CA2719884A1 - Analyte sensor calibration management - Google Patents
Analyte sensor calibration management Download PDFInfo
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- CA2719884A1 CA2719884A1 CA2719884A CA2719884A CA2719884A1 CA 2719884 A1 CA2719884 A1 CA 2719884A1 CA 2719884 A CA2719884 A CA 2719884A CA 2719884 A CA2719884 A CA 2719884A CA 2719884 A1 CA2719884 A1 CA 2719884A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1495—Calibrating or testing of in-vivo probes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14503—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1486—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using enzyme electrodes, e.g. with immobilised oxidase
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
- A61B2560/02—Operational features
- A61B2560/0223—Operational features of calibration, e.g. protocols for calibrating sensors
Abstract
Methods and devices to detect analyte in body fluid are provided. Embodiments include positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period, managing if and when to request additional reference signal measurements, and managing if and when to temporarily not display results.
Description
ANALYTE SENSOR CALIBRATION MANAGEMENT
PRIORITY
The present application claims priority to U.S. patent application no.
12/363,712 filed January 30, 2009 entitled "Analyte Sensor Calibration Management"
and to U.S. provisional application no. 61/040,633 filed March 28, 2008 entitled "Analyte Sensor Calibration Management", both of which are assigned to the assignee of the present application, Abbott Diabetes Care Inc., of Alameda, California, and the disclosures of each of which are incorporated herein by reference for all purposes.
BACKGROUND
The detection of the level of glucose or other analytes, such as lactate, oxygen or the like, in certain individuals is vitally important to their health. For example, the monitoring of glucose is particularly important to individuals with diabetes.
Diabetics may need to monitor glucose levels to determine when insulin is needed to reduce glucose levels in their bodies or when additional glucose is needed to raise the level of glucose in their bodies.
Devices have been developed for continuous or automatic monitoring of analytes, such as glucose, in bodily fluid such as in the blood stream or in interstitial fluid. Some of these analyte measuring devices are configured so that at least a portion of the devices are positioned below a skin surface of a user, e.g., in a blood vessel or in the subcutaneous tissue of a user.
Following the sensor insertion, the resulting potential trauma to the skin and/or underlying tissue, for example, by the sensor introducer and/or the sensor itself, may, at times, result in instability of signals monitored by the sensor. This may occur in a number of analyte sensors, but not in all cases. This instability is characterized by a decrease in the sensor signal, and when this occurs, generally, the analyte levels monitored may not be reported, recorded or output to the user.
Proper calibration of an analyte sensor with a reference glucose measurement or reading is important for accurate sensor performance. Calibration is a process by which a conversion factor (or sensitivity) is determined and represented, in its simplest form, as a ratio of the electrical current generated by the analyte sensor to the reference blood glucose value (for example, from an in vitro blood glucose meter) associated in time (for example, relatively time corresponding) with the current signal from the analyte sensor. Ideally, the sensitivity is constant throughout the life of the analyte sensor when positioned in fluid contact with an analyte of a user (such as interstitial fluid). In practice, however, the sensitivity may vary over time.
It has been observed that a depression or attenuation in the sensitivity, usually following a predetermined time period measured from the insertion or positioning of the analyte sensor occurs sometimes up to 24 hours for some analyte sensors. This signal characteristic is referred to as Early Sensitivity Attenuation (ESA) or referred to as ESA condition. The ESA condition may be a result of a physiological response to the introduction of the analyte sensor to the subcutaneous tissue, and may be present for any subcutaneously inserted analyte sensor.
Generally, the use of a standard calibration sensitivity calculation does not address the signal attenuation. A typical standard calibration does not detect or manage the attenuated signal characteristics, and also may potentially update or modify the calibration sensitivity using the erroneous and attenuated sensor signal.
When sensor calibration is performed while the sensor is undergoing a signal attenuation event, the reported or resulting sensor data may be erroneously high when the sensor sensitivity has recovered after the termination of the signal attenuation event. Such high biased results may be clinically unsafe, as they may lead to missed hypoglycaemic events, or overdoses of medication such as insulin. On the other hand, when sensor calibration is performed prior to an early signal attenuation event, erroneously low biased sensor data will likely result during the period of the sensor sensitivity depression. Such low glucose results may, depending on the magnitude of the early signal attenuation event, result in false hypoglycaemia alarms or missed hyperglycaemic events.
Another approach has been to delay the sensor calibration until after the early signal attenuation period measured, for example, from the initial sensor insertion in the patient. However, this approach prevents the reporting of the potentially erroneous analyte level monitored from the sensor during this period, but results in low data yield due to the undesirable delay for the display or reporting of the monitored analyte levels from the sensors regardless of whether or not early signal attenuation is present.
PRIORITY
The present application claims priority to U.S. patent application no.
12/363,712 filed January 30, 2009 entitled "Analyte Sensor Calibration Management"
and to U.S. provisional application no. 61/040,633 filed March 28, 2008 entitled "Analyte Sensor Calibration Management", both of which are assigned to the assignee of the present application, Abbott Diabetes Care Inc., of Alameda, California, and the disclosures of each of which are incorporated herein by reference for all purposes.
BACKGROUND
The detection of the level of glucose or other analytes, such as lactate, oxygen or the like, in certain individuals is vitally important to their health. For example, the monitoring of glucose is particularly important to individuals with diabetes.
Diabetics may need to monitor glucose levels to determine when insulin is needed to reduce glucose levels in their bodies or when additional glucose is needed to raise the level of glucose in their bodies.
Devices have been developed for continuous or automatic monitoring of analytes, such as glucose, in bodily fluid such as in the blood stream or in interstitial fluid. Some of these analyte measuring devices are configured so that at least a portion of the devices are positioned below a skin surface of a user, e.g., in a blood vessel or in the subcutaneous tissue of a user.
Following the sensor insertion, the resulting potential trauma to the skin and/or underlying tissue, for example, by the sensor introducer and/or the sensor itself, may, at times, result in instability of signals monitored by the sensor. This may occur in a number of analyte sensors, but not in all cases. This instability is characterized by a decrease in the sensor signal, and when this occurs, generally, the analyte levels monitored may not be reported, recorded or output to the user.
Proper calibration of an analyte sensor with a reference glucose measurement or reading is important for accurate sensor performance. Calibration is a process by which a conversion factor (or sensitivity) is determined and represented, in its simplest form, as a ratio of the electrical current generated by the analyte sensor to the reference blood glucose value (for example, from an in vitro blood glucose meter) associated in time (for example, relatively time corresponding) with the current signal from the analyte sensor. Ideally, the sensitivity is constant throughout the life of the analyte sensor when positioned in fluid contact with an analyte of a user (such as interstitial fluid). In practice, however, the sensitivity may vary over time.
It has been observed that a depression or attenuation in the sensitivity, usually following a predetermined time period measured from the insertion or positioning of the analyte sensor occurs sometimes up to 24 hours for some analyte sensors. This signal characteristic is referred to as Early Sensitivity Attenuation (ESA) or referred to as ESA condition. The ESA condition may be a result of a physiological response to the introduction of the analyte sensor to the subcutaneous tissue, and may be present for any subcutaneously inserted analyte sensor.
Generally, the use of a standard calibration sensitivity calculation does not address the signal attenuation. A typical standard calibration does not detect or manage the attenuated signal characteristics, and also may potentially update or modify the calibration sensitivity using the erroneous and attenuated sensor signal.
When sensor calibration is performed while the sensor is undergoing a signal attenuation event, the reported or resulting sensor data may be erroneously high when the sensor sensitivity has recovered after the termination of the signal attenuation event. Such high biased results may be clinically unsafe, as they may lead to missed hypoglycaemic events, or overdoses of medication such as insulin. On the other hand, when sensor calibration is performed prior to an early signal attenuation event, erroneously low biased sensor data will likely result during the period of the sensor sensitivity depression. Such low glucose results may, depending on the magnitude of the early signal attenuation event, result in false hypoglycaemia alarms or missed hyperglycaemic events.
Another approach has been to delay the sensor calibration until after the early signal attenuation period measured, for example, from the initial sensor insertion in the patient. However, this approach prevents the reporting of the potentially erroneous analyte level monitored from the sensor during this period, but results in low data yield due to the undesirable delay for the display or reporting of the monitored analyte levels from the sensors regardless of whether or not early signal attenuation is present.
SUMMARY
Embodiments of the subject disclosure include device and methods of detecting a change, e.g., a decrease (or monitoring for a change in the signal level), in sensitivity associated with an analyte sensor to identify or detect early signal attenuation (ESA). The detected or monitored analyte level is reported or output after a short sensor equilibration time period (e.g., approximately one hour or more or less) when detected change is not associated with early signal attenuation.
Also provided are systems, computer program products, and kits.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows a block diagram of an embodiment of a data monitoring and management system according to the present disclosure;
FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1;
FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit of the data monitoring and management system of FIG. 1;
FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor according to the present disclosure;
FIGS. 5A-5B show a perspective view and a cross sectional view, respectively of an embodiment the analyte sensor of FIG. 4;
FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure;
FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure;
FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure; and FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure.
DETAILED DESCRIPTION
Within the scope of the present disclosure, early signal attenuation (ESA) condition which may be attributable to associated instability of monitored analyte levels resulting from skin and/or tissue trauma when the sensor is transcutaneously positioned under the skin layer of a user. Analyte sensors may be manufactured and/or the trauma resulting from the inserted sensor may be such that the sensor attains a stability point or an equilibration level after a relatively short time period -for example, within approximately one hour (or less) from the initial sensor insertion.
In one aspect, the signals from the analyte sensor may be monitored for ESA
condition detection. When no ESA condition is detected and/or the sensor reaches the equilibration level within the short time period, then the analyte monitoring system may be configured to request a reference blood glucose value from the user, for example, a fingerstick in vitro test using a blood glucose meter, to calibrate the sensor signals, and thereafter, report or display to the user the monitored analyte levels. In this manner, in one aspect, the initial baseline calibration of the analyte sensor may be performed after approximately one hour from the initial sensor insertion, and upon successful calibration, the resulting real time analyte levels displayed to the user, or otherwise stored or logged in the analyte monitoring system and/or transmitted to a remote device or terminal.
When the potential for ESA condition or actual ESA condition is detected after the initial equilibration time period, for example, of approximately one hour from the sensor insertion, the analyte monitoring system may be configured to alert the user to wait a predetermined time period before providing the reference blood glucose value to provide the sensor to stabilize, or alternatively, the user may be prompted to provide the reference blood glucose value to confirm whether the potential ESA condition monitored is an actual occurrence of ESA condition.
In one aspect, the scheduled calibration of the analyte sensor may be delayed to provide the sensor additional time period to reach a desired or acceptable stability level. Among other conditions, boundaries may be established to provide the sensor additional time to reach a predetermined or acceptable stability level before the received analyte sensor signals are calibrated, and thus, provided to the user. Within the scope of the present disclosure, other conditions and parameters may be provided to establish or detect ESA condition during a predetermined time period from the initial sensor insertion, for example, during the first 24 hours of sensor insertion.
In this manner, in one aspect, when it is determined that the transcutaneously positioned sensor has reached an acceptable stability level resulting in the desired or predetermined equilibration level, the analyte monitoring system may display or otherwise accept, output, log, or process the monitored analyte level, substantially in real time, received from the transcutaneously positioned sensor. In one aspect, the acceptable stability level is analyzed at approximately one hour from the initial sensor insertion, and thereafter, when no ESA condition is detected, the analyte sensor data is calibrated against a reference blood glucose value (for example, received from an in vitro glucose meter).
In the case where ESA condition or the potential for such signal attenuation is detected, the analyte monitoring system may be configured in one embodiment to perform one or more routines or functions to verify the sensor related signals to confirm the ESA condition, to notify the user to refrain from performing a fingerstick test using a blood glucose meter to provide a reference blood glucose value for calibration, among others.
Before the present disclosure is described in additional detail, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure.
The upper and lower limits of these smaller ranges may independently be included in the smaller ranges also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, the preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited.
It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise.
The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present disclosure is not entitled to antedate such publication by virtue of prior disclosure. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.
As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure.
The figures shown herein are not necessarily drawn to scale, with some components and features being exaggerated for clarity.
Generally, embodiments of the present disclosure relate to methods and devices for detecting at least one analyte such as glucose in body fluid. In certain embodiments, the present disclosure relates to the continuous and/or automatic in vivo monitoring of the level of one or more analyte using a continuous analyte monitoring system that includes an analyte sensor at least a portion of which is to be positioned beneath a skin surface of a user for a period of time and/or the discrete monitoring of one or more analytes using an in vitro blood glucose ("BG") meter and an analyte test strip. Embodiments include combined or combinable devices, systems and methods and/or transferring data between an in vivo continuous system and a BG meter system.
Accordingly, embodiments include analyte monitoring devices and systems that include an analyte sensor- at least a portion of which is positionable beneath the skin of the user - for the in vivo detection, of an analyte, such as glucose, lactate, and the like, in a body fluid. Embodiments include wholly implantable analyte sensors and analyte sensors in which only a portion of the sensor is positioned under the skin and a portion of the sensor resides above the skin, e.g., for contact to a transmitter, receiver, transceiver, processor, etc. The sensor may be, for example, subcutaneously positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's interstitial fluid. For the purposes of this description, continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise. The sensor response may be correlated and/or converted to analyte levels in blood or other fluids. In certain embodiments, an analyte sensor may be positioned in contact with interstitial fluid to detect the level of glucose, which detected glucose may be used to infer the glucose level in the patient's bloodstream. Analyte sensors may be insertable into a vein, artery, or other portion of the body containing fluid.
Embodiments of the analyte sensors of the subject disclosure may be configured for monitoring the level of the analyte over a time period which may range from minutes, hours, days, weeks, or longer.
Of interest are analyte sensors, such as glucose sensors, that are capable of in vivo detection of an analyte for about one hour or more, e.g., about a few hours or more, e.g., about a few days of more, e.g., about three or more days, e.g., about five days or more, e.g., about seven days or more, e.g., about several weeks or at least one month. Future analyte levels may be predicted based on information obtained, e.g., the current analyte level at time to, the rate of change of the analyte, etc.
Predictive alarms may notify the user of predicted analyte levels that may be of concern prior in advance of the analyte level reaching the future level. This enables the user an opportunity to take corrective action.
FIG. 1 shows a data monitoring and management system such as, for example, an analyte (e.g., glucose) monitoring system 100 in accordance with certain embodiments. Embodiments of the subject disclosure are further described primarily with respect to glucose monitoring devices and systems, and methods of glucose detection, for convenience only and such description is in no way intended to limit the scope of the disclosure. It is to be understood that the analyte monitoring system may be configured to monitor a variety of analytes at the same time or at different times.
Analytes that may be monitored include, but are not limited to, acetyl choline, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketone bodies, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin. The concentration of drugs, such as, for example, antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of abuse, theophylline, and warfarin, may also be monitored. In those embodiments that monitor more than one analyte, the analytes may be monitored at the same or different times.
The analyte monitoring system 100 includes a sensor 101, a data processing unit 102 connectable to the sensor 101, and a primary receiver unit 104 which is configured to communicate with the data processing unit 102 via a communication link 103. In certain embodiments, the primary receiver unit 104 may be further configured to transmit data to a data processing terminal 105 to evaluate or otherwise process or format data received by the primary receiver unit 104. The data processing terminal 105 may be configured to receive data directly from the data processing unit 102 via a communication link which may optionally be configured for bi-directional communication. Further, the data processing unit 102 may include a transmitter or a transceiver to transmit and/or receive data to and/or from the primary receiver unit 104, and/or the data processing terminal 105 and/or optionally the secondary receiver unit 106.
Also shown in FIG. 1 is an optional secondary receiver unit 106 which is operatively coupled to the communication link and configured to receive data transmitted from the data processing unit 102. The secondary receiver unit 106 may be configured to communicate with the primary receiver unit 104, as well as the data processing terminal 105. The secondary receiver unit 106 may be configured for bi-directional wireless communication with each of the primary receiver unit 104 and the data processing terminal 105. As discussed in further detail below, in certain embodiments the secondary receiver unit 106 may be a de-featured receiver as compared to the primary receiver, i.e., the secondary receiver may include a limited or minimal number of functions and features as compared with the primary receiver unit 104. As such, the secondary receiver unit 106 may include a smaller (in one or more, including all, dimensions), compact housing or embodied in a device such as a wrist watch, arm band, etc., for example. Alternatively, the secondary receiver unit may be configured with the same or substantially similar functions and features as the primary receiver unit 104. The secondary receiver unit 106 may include a docking portion to be mated with a docking cradle unit for placement by, e.g., the bedside for night time monitoring, and/or bi-directional communication device. A docking cradle may recharge a power supply.
Embodiments of the subject disclosure include device and methods of detecting a change, e.g., a decrease (or monitoring for a change in the signal level), in sensitivity associated with an analyte sensor to identify or detect early signal attenuation (ESA). The detected or monitored analyte level is reported or output after a short sensor equilibration time period (e.g., approximately one hour or more or less) when detected change is not associated with early signal attenuation.
Also provided are systems, computer program products, and kits.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows a block diagram of an embodiment of a data monitoring and management system according to the present disclosure;
FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1;
FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit of the data monitoring and management system of FIG. 1;
FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor according to the present disclosure;
FIGS. 5A-5B show a perspective view and a cross sectional view, respectively of an embodiment the analyte sensor of FIG. 4;
FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure;
FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure;
FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure; and FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure.
DETAILED DESCRIPTION
Within the scope of the present disclosure, early signal attenuation (ESA) condition which may be attributable to associated instability of monitored analyte levels resulting from skin and/or tissue trauma when the sensor is transcutaneously positioned under the skin layer of a user. Analyte sensors may be manufactured and/or the trauma resulting from the inserted sensor may be such that the sensor attains a stability point or an equilibration level after a relatively short time period -for example, within approximately one hour (or less) from the initial sensor insertion.
In one aspect, the signals from the analyte sensor may be monitored for ESA
condition detection. When no ESA condition is detected and/or the sensor reaches the equilibration level within the short time period, then the analyte monitoring system may be configured to request a reference blood glucose value from the user, for example, a fingerstick in vitro test using a blood glucose meter, to calibrate the sensor signals, and thereafter, report or display to the user the monitored analyte levels. In this manner, in one aspect, the initial baseline calibration of the analyte sensor may be performed after approximately one hour from the initial sensor insertion, and upon successful calibration, the resulting real time analyte levels displayed to the user, or otherwise stored or logged in the analyte monitoring system and/or transmitted to a remote device or terminal.
When the potential for ESA condition or actual ESA condition is detected after the initial equilibration time period, for example, of approximately one hour from the sensor insertion, the analyte monitoring system may be configured to alert the user to wait a predetermined time period before providing the reference blood glucose value to provide the sensor to stabilize, or alternatively, the user may be prompted to provide the reference blood glucose value to confirm whether the potential ESA condition monitored is an actual occurrence of ESA condition.
In one aspect, the scheduled calibration of the analyte sensor may be delayed to provide the sensor additional time period to reach a desired or acceptable stability level. Among other conditions, boundaries may be established to provide the sensor additional time to reach a predetermined or acceptable stability level before the received analyte sensor signals are calibrated, and thus, provided to the user. Within the scope of the present disclosure, other conditions and parameters may be provided to establish or detect ESA condition during a predetermined time period from the initial sensor insertion, for example, during the first 24 hours of sensor insertion.
In this manner, in one aspect, when it is determined that the transcutaneously positioned sensor has reached an acceptable stability level resulting in the desired or predetermined equilibration level, the analyte monitoring system may display or otherwise accept, output, log, or process the monitored analyte level, substantially in real time, received from the transcutaneously positioned sensor. In one aspect, the acceptable stability level is analyzed at approximately one hour from the initial sensor insertion, and thereafter, when no ESA condition is detected, the analyte sensor data is calibrated against a reference blood glucose value (for example, received from an in vitro glucose meter).
In the case where ESA condition or the potential for such signal attenuation is detected, the analyte monitoring system may be configured in one embodiment to perform one or more routines or functions to verify the sensor related signals to confirm the ESA condition, to notify the user to refrain from performing a fingerstick test using a blood glucose meter to provide a reference blood glucose value for calibration, among others.
Before the present disclosure is described in additional detail, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure.
The upper and lower limits of these smaller ranges may independently be included in the smaller ranges also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, the preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited.
It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise.
The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present disclosure is not entitled to antedate such publication by virtue of prior disclosure. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.
As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure.
The figures shown herein are not necessarily drawn to scale, with some components and features being exaggerated for clarity.
Generally, embodiments of the present disclosure relate to methods and devices for detecting at least one analyte such as glucose in body fluid. In certain embodiments, the present disclosure relates to the continuous and/or automatic in vivo monitoring of the level of one or more analyte using a continuous analyte monitoring system that includes an analyte sensor at least a portion of which is to be positioned beneath a skin surface of a user for a period of time and/or the discrete monitoring of one or more analytes using an in vitro blood glucose ("BG") meter and an analyte test strip. Embodiments include combined or combinable devices, systems and methods and/or transferring data between an in vivo continuous system and a BG meter system.
Accordingly, embodiments include analyte monitoring devices and systems that include an analyte sensor- at least a portion of which is positionable beneath the skin of the user - for the in vivo detection, of an analyte, such as glucose, lactate, and the like, in a body fluid. Embodiments include wholly implantable analyte sensors and analyte sensors in which only a portion of the sensor is positioned under the skin and a portion of the sensor resides above the skin, e.g., for contact to a transmitter, receiver, transceiver, processor, etc. The sensor may be, for example, subcutaneously positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's interstitial fluid. For the purposes of this description, continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise. The sensor response may be correlated and/or converted to analyte levels in blood or other fluids. In certain embodiments, an analyte sensor may be positioned in contact with interstitial fluid to detect the level of glucose, which detected glucose may be used to infer the glucose level in the patient's bloodstream. Analyte sensors may be insertable into a vein, artery, or other portion of the body containing fluid.
Embodiments of the analyte sensors of the subject disclosure may be configured for monitoring the level of the analyte over a time period which may range from minutes, hours, days, weeks, or longer.
Of interest are analyte sensors, such as glucose sensors, that are capable of in vivo detection of an analyte for about one hour or more, e.g., about a few hours or more, e.g., about a few days of more, e.g., about three or more days, e.g., about five days or more, e.g., about seven days or more, e.g., about several weeks or at least one month. Future analyte levels may be predicted based on information obtained, e.g., the current analyte level at time to, the rate of change of the analyte, etc.
Predictive alarms may notify the user of predicted analyte levels that may be of concern prior in advance of the analyte level reaching the future level. This enables the user an opportunity to take corrective action.
FIG. 1 shows a data monitoring and management system such as, for example, an analyte (e.g., glucose) monitoring system 100 in accordance with certain embodiments. Embodiments of the subject disclosure are further described primarily with respect to glucose monitoring devices and systems, and methods of glucose detection, for convenience only and such description is in no way intended to limit the scope of the disclosure. It is to be understood that the analyte monitoring system may be configured to monitor a variety of analytes at the same time or at different times.
Analytes that may be monitored include, but are not limited to, acetyl choline, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketone bodies, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin. The concentration of drugs, such as, for example, antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of abuse, theophylline, and warfarin, may also be monitored. In those embodiments that monitor more than one analyte, the analytes may be monitored at the same or different times.
The analyte monitoring system 100 includes a sensor 101, a data processing unit 102 connectable to the sensor 101, and a primary receiver unit 104 which is configured to communicate with the data processing unit 102 via a communication link 103. In certain embodiments, the primary receiver unit 104 may be further configured to transmit data to a data processing terminal 105 to evaluate or otherwise process or format data received by the primary receiver unit 104. The data processing terminal 105 may be configured to receive data directly from the data processing unit 102 via a communication link which may optionally be configured for bi-directional communication. Further, the data processing unit 102 may include a transmitter or a transceiver to transmit and/or receive data to and/or from the primary receiver unit 104, and/or the data processing terminal 105 and/or optionally the secondary receiver unit 106.
Also shown in FIG. 1 is an optional secondary receiver unit 106 which is operatively coupled to the communication link and configured to receive data transmitted from the data processing unit 102. The secondary receiver unit 106 may be configured to communicate with the primary receiver unit 104, as well as the data processing terminal 105. The secondary receiver unit 106 may be configured for bi-directional wireless communication with each of the primary receiver unit 104 and the data processing terminal 105. As discussed in further detail below, in certain embodiments the secondary receiver unit 106 may be a de-featured receiver as compared to the primary receiver, i.e., the secondary receiver may include a limited or minimal number of functions and features as compared with the primary receiver unit 104. As such, the secondary receiver unit 106 may include a smaller (in one or more, including all, dimensions), compact housing or embodied in a device such as a wrist watch, arm band, etc., for example. Alternatively, the secondary receiver unit may be configured with the same or substantially similar functions and features as the primary receiver unit 104. The secondary receiver unit 106 may include a docking portion to be mated with a docking cradle unit for placement by, e.g., the bedside for night time monitoring, and/or bi-directional communication device. A docking cradle may recharge a power supply.
Only one sensor 101, data processing unit 102 and data processing terminal 105 are shown in the embodiment of the analyte monitoring system 100 illustrated in FIG. 1. However, it will be appreciated by one of ordinary skill in the art that the analyte monitoring system 100 may include more than one sensor 101 and/or more than one data processing unit 102, and/or more than one data processing terminal 105.
Multiple sensors may be positioned in a patient for analyte monitoring at the same or different times. In certain embodiments, analyte information obtained by a first positioned sensor may be employed as a comparison to analyte information obtained by a second sensor. This may be useful to confirm or validate analyte information obtained from one or both of the sensors. Such redundancy may be useful if analyte information is contemplated in critical therapy-related decisions. In certain embodiments, a first sensor may be used to calibrate a second sensor.
The analyte monitoring system 100 may be a continuous monitoring system, or semi-continuous, or a discrete monitoring system. In a multi-component environment, each component may be configured to be uniquely identified by one or more of the other components in the system so that communication conflict may be readily resolved between the various components within the analyte monitoring system 100. For example, unique IDs, communication channels, and the like, may be used.
In certain embodiments, the sensor 101 is physically positioned in or on the body of a user whose analyte level is being monitored. The sensor 101 may be configured to at least periodically sample the analyte level of the user and convert the sampled analyte level into a corresponding signal for transmission by the data processing unit 102. The data processing unit 102 is coupleable to the sensor 101 so that both devices are positioned in or on the user's body, with at least a portion of the analyte sensor 101 positioned transcutaneously. The data processing unit 102 may include a fixation element such as adhesive or the like to secure it to the user's body.
A mount (not shown) attachable to the user and mateable with the unit 102 may be used. For example, a mount may include an adhesive surface. The data processing unit 102 performs data processing functions, where such functions may include but are not limited to, filtering and encoding of data signals, each of which corresponds to a sampled analyte level of the user, for transmission to the primary receiver unit 104 via the communication link 103. In one embodiment, the sensor 101 or the data processing unit 102 or a combined sensor/data processing unit may be wholly implantable under the skin layer of the user.
In one aspect, the primary receiver unit 104 may include an analog interface section including an RF receiver and an antenna that is configured to communicate with the data processing unit 102 via the communication link 103, and a data processing section for processing the received data from the data processing unit 102 such as data decoding, error detection and correction, data clock generation, data bit recovery, etc., or any combination thereof.
In operation, the primary receiver unit 104 in certain embodiments is configured to synchronize with the data processing unit 102 to uniquely identify the data processing unit 102, based on, for example, an identification information of the data processing unit 102, and thereafter, to periodically receive signals transmitted from the data processing unit 102 associated with the monitored analyte levels detected by the sensor 101.
Referring again to FIG. 1, the data processing terminal 105 may include a personal computer, a portable computer such as a laptop or a handheld device (e.g., personal digital assistants (PDAs), telephone such as a cellular phone (e.g., a multimedia and Internet-enabled mobile phone such as an iPhone or similar phone), mp3 player, pager, and the like), or drug delivery device, each of which may be configured for data communication with the receiver via a wired or a wireless connection. Additionally, the data processing terminal 105 may further be connected to a data network (not shown) for storing, retrieving, updating, and/or analyzing data corresponding to the detected analyte level of the user.
The data processing terminal 105 may include an infusion device such as an insulin infusion pump or the like, which may be configured to administer insulin to patients, and which may be configured to communicate with the primary receiver unit 104 for receiving, among others, the measured analyte level. Alternatively, the primary receiver unit 104 may be configured to integrate an infusion device therein so that the primary receiver unit 104 is configured to administer insulin (or other appropriate drug) therapy to patients, for example, for administering and modifying basal profiles, as well as for determining appropriate boluses for administration based on, among others, the detected analyte levels received from the data processing unit 102. An infusion device may be an external device or an internal device (wholly implantable in a user).
In particular embodiments, the data processing terminal 105, which may include an insulin pump, may be configured to receive the analyte signals from the data processing unit 102, and thus, incorporate the functions of the primary receiver unit 104 including data processing for managing the patient's insulin therapy and analyte monitoring. In certain embodiments, the communication link 103 as well as one or more of the other communication interfaces shown in FIG. 1, may use one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an 802.1 lx wireless communication protocol, or an equivalent wireless communication protocol which would allow secure, wireless communication of several units (for example, per HIPPA
requirements) while avoiding potential data collision and interference.
FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1. The data processing unit thus may include one or more of an analog interface 201 configured to communicate with the sensor 101 (FIG. 1), a user input 202, and a temperature measurement section 203, each of which is operatively coupled to a processor 204 such as a central processing unit (CPU). The data processing unit 102 may include user input and/or interface components or may be free of user input and/or interface components.
In certain embodiments, one or more application-specific integrated circuits (ASIC) may be used to implement one or more functions or routines associated with the operations of the data processing unit (and/or receiver unit) using for example one or more state machines and buffers.
Further shown in FIG. 2 is a serial communication section 205 which is operatively coupled to the processor 204. In one embodiment, the data processing unit 102 may include a bi-directional communication link 209 between the analog interface 201 and the serial communication section 205.
In certain embodiments, the data processing unit includes an RF transmitter 206, which is also operatively coupled to the processor 204. The RF
transmitter 206, in some embodiments, may be configured as an RF receiver or an RF
transmitter/receiver, such as a transceiver. Moreover, a power supply 207, such as a battery, may also be provided in the data processing unit 102 to provide the necessary power for the data processing unit 102. Additionally, as can be seen from the Figure, clock 208 may be provided to, among others, supply real time information to the processor 204.
As can be seen in the embodiment of FIG. 2, the sensor unit 101 (FIG. 1) includes four contacts, three of which are electrodes - work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213, each operatively coupled to the analog interface 201 of the data processing unit 102. In certain embodiments, each of the work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213 may be made using a conductive material that may be applied by, e.g., chemical vapor deposition (CVD), physical vapor deposition, sputtering, reactive sputtering, printing, coating, ablating (e.g., laser ablation), painting, dip coating, etching, and the like.
Materials include but are not limited to aluminum, carbon (such as graphite), cobalt, copper, gallium, gold, indium, iridium, iron, lead, magnesium, mercury (as an amalgam), nickel, niobium, osmium, palladium, platinum, rhenium, rhodium, selenium, silicon (e.g., doped polycrystalline silicon), silver, tantalum, tin, titanium, tungsten, uranium, vanadium, zinc, zirconium, mixtures thereof, and alloys, oxides, or metallic compounds of these elements.
The processor 204 may be configured to generate and/or process control signals to the various sections of the data processing unit 102 during the operation of the data processing unit 102. In certain embodiments, the processor 204 also includes memory (not shown) for storing data such as the identification information for the data processing unit 102, as well as the data associated with signals received from the sensor 101. The stored information may be retrieved and processed for transmission to the primary receiver unit 104 under the control of the processor 204.
Furthermore, the power supply 207 may include a commercially available battery.
In certain embodiments, a manufacturing process of the data processing unit 102 may place the data processing unit 102 in the lower power, non-operating state (i.e., post-manufacture sleep mode). In this manner, the shelf life of the data processing unit 102 may be significantly improved. Moreover, as shown in FIG.
2, while the power supply unit 207 is shown as coupled to the processor 204, and as such, the processor 204 is configured to provide control of the power supply unit 207, it should be noted that within the scope of the present disclosure, the power supply unit 207 is configured to provide the necessary power to each of the components of the data processing unit 102 shown in FIG. 2.
Referring back to FIG. 2, the power supply section 207 of the data processing unit 102 in one embodiment may include a rechargeable battery unit that may be recharged by a separate power supply recharging unit (for example, provided in the receiver unit 104) so that the data processing unit 102 may be powered for a longer period of usage time. In certain embodiments, the data processing unit 102 may be configured without a battery in the power supply section 207, in which case the data processing unit 102 may be configured to receive power from an external power supply source (for example, a battery, electrical outlet, etc.) as discussed in further detail below.
Referring yet again to FIG. 2, a temperature detection section 203 of the data processing unit 102 is configured to monitor the temperature of the skin near the sensor insertion site. The temperature reading may be used to adjust the analyte readings obtained from the analog interface 201. Also shown is a leak detection circuit 214 coupled to the guard trace (G) 211 and the processor 204 in the data processing unit 102 of the data monitoring and management system 100. The leak detection circuit 214 may be configured to detect leakage current in the sensor 101 to determine whether the measured sensor data are corrupt or whether the measured data from the sensor 101 is accurate. Such detection may trigger a notification to the user.
FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit, such as the primary receiver unit 104, of the data monitoring and management system shown in FIG. 1. The primary receiver unit 104 includes one or more of. a blood glucose test strip interface 301, an RF receiver 302, an input 303, a temperature monitor section 304, and a clock 305, each of which are operatively coupled to a processing and storage section 307. The primary receiver unit 104 also includes a power supply 306 operatively coupled to a power conversion and monitoring section 308. Further, the power conversion and monitoring section 308 is also coupled to the receiver processing and storage section 307. Moreover, also shown are a receiver serial communication section 309, and an output 310, each operatively coupled to the processing and storage unit 307. The receiver may include user input and/or interface components or may be free of user input and/or interface components.
Multiple sensors may be positioned in a patient for analyte monitoring at the same or different times. In certain embodiments, analyte information obtained by a first positioned sensor may be employed as a comparison to analyte information obtained by a second sensor. This may be useful to confirm or validate analyte information obtained from one or both of the sensors. Such redundancy may be useful if analyte information is contemplated in critical therapy-related decisions. In certain embodiments, a first sensor may be used to calibrate a second sensor.
The analyte monitoring system 100 may be a continuous monitoring system, or semi-continuous, or a discrete monitoring system. In a multi-component environment, each component may be configured to be uniquely identified by one or more of the other components in the system so that communication conflict may be readily resolved between the various components within the analyte monitoring system 100. For example, unique IDs, communication channels, and the like, may be used.
In certain embodiments, the sensor 101 is physically positioned in or on the body of a user whose analyte level is being monitored. The sensor 101 may be configured to at least periodically sample the analyte level of the user and convert the sampled analyte level into a corresponding signal for transmission by the data processing unit 102. The data processing unit 102 is coupleable to the sensor 101 so that both devices are positioned in or on the user's body, with at least a portion of the analyte sensor 101 positioned transcutaneously. The data processing unit 102 may include a fixation element such as adhesive or the like to secure it to the user's body.
A mount (not shown) attachable to the user and mateable with the unit 102 may be used. For example, a mount may include an adhesive surface. The data processing unit 102 performs data processing functions, where such functions may include but are not limited to, filtering and encoding of data signals, each of which corresponds to a sampled analyte level of the user, for transmission to the primary receiver unit 104 via the communication link 103. In one embodiment, the sensor 101 or the data processing unit 102 or a combined sensor/data processing unit may be wholly implantable under the skin layer of the user.
In one aspect, the primary receiver unit 104 may include an analog interface section including an RF receiver and an antenna that is configured to communicate with the data processing unit 102 via the communication link 103, and a data processing section for processing the received data from the data processing unit 102 such as data decoding, error detection and correction, data clock generation, data bit recovery, etc., or any combination thereof.
In operation, the primary receiver unit 104 in certain embodiments is configured to synchronize with the data processing unit 102 to uniquely identify the data processing unit 102, based on, for example, an identification information of the data processing unit 102, and thereafter, to periodically receive signals transmitted from the data processing unit 102 associated with the monitored analyte levels detected by the sensor 101.
Referring again to FIG. 1, the data processing terminal 105 may include a personal computer, a portable computer such as a laptop or a handheld device (e.g., personal digital assistants (PDAs), telephone such as a cellular phone (e.g., a multimedia and Internet-enabled mobile phone such as an iPhone or similar phone), mp3 player, pager, and the like), or drug delivery device, each of which may be configured for data communication with the receiver via a wired or a wireless connection. Additionally, the data processing terminal 105 may further be connected to a data network (not shown) for storing, retrieving, updating, and/or analyzing data corresponding to the detected analyte level of the user.
The data processing terminal 105 may include an infusion device such as an insulin infusion pump or the like, which may be configured to administer insulin to patients, and which may be configured to communicate with the primary receiver unit 104 for receiving, among others, the measured analyte level. Alternatively, the primary receiver unit 104 may be configured to integrate an infusion device therein so that the primary receiver unit 104 is configured to administer insulin (or other appropriate drug) therapy to patients, for example, for administering and modifying basal profiles, as well as for determining appropriate boluses for administration based on, among others, the detected analyte levels received from the data processing unit 102. An infusion device may be an external device or an internal device (wholly implantable in a user).
In particular embodiments, the data processing terminal 105, which may include an insulin pump, may be configured to receive the analyte signals from the data processing unit 102, and thus, incorporate the functions of the primary receiver unit 104 including data processing for managing the patient's insulin therapy and analyte monitoring. In certain embodiments, the communication link 103 as well as one or more of the other communication interfaces shown in FIG. 1, may use one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an 802.1 lx wireless communication protocol, or an equivalent wireless communication protocol which would allow secure, wireless communication of several units (for example, per HIPPA
requirements) while avoiding potential data collision and interference.
FIG. 2 shows a block diagram of an embodiment of the data processing unit of the data monitoring and management system of FIG. 1. The data processing unit thus may include one or more of an analog interface 201 configured to communicate with the sensor 101 (FIG. 1), a user input 202, and a temperature measurement section 203, each of which is operatively coupled to a processor 204 such as a central processing unit (CPU). The data processing unit 102 may include user input and/or interface components or may be free of user input and/or interface components.
In certain embodiments, one or more application-specific integrated circuits (ASIC) may be used to implement one or more functions or routines associated with the operations of the data processing unit (and/or receiver unit) using for example one or more state machines and buffers.
Further shown in FIG. 2 is a serial communication section 205 which is operatively coupled to the processor 204. In one embodiment, the data processing unit 102 may include a bi-directional communication link 209 between the analog interface 201 and the serial communication section 205.
In certain embodiments, the data processing unit includes an RF transmitter 206, which is also operatively coupled to the processor 204. The RF
transmitter 206, in some embodiments, may be configured as an RF receiver or an RF
transmitter/receiver, such as a transceiver. Moreover, a power supply 207, such as a battery, may also be provided in the data processing unit 102 to provide the necessary power for the data processing unit 102. Additionally, as can be seen from the Figure, clock 208 may be provided to, among others, supply real time information to the processor 204.
As can be seen in the embodiment of FIG. 2, the sensor unit 101 (FIG. 1) includes four contacts, three of which are electrodes - work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213, each operatively coupled to the analog interface 201 of the data processing unit 102. In certain embodiments, each of the work electrode (W) 210, guard contact (G) 211, reference electrode (R) 212, and counter electrode (C) 213 may be made using a conductive material that may be applied by, e.g., chemical vapor deposition (CVD), physical vapor deposition, sputtering, reactive sputtering, printing, coating, ablating (e.g., laser ablation), painting, dip coating, etching, and the like.
Materials include but are not limited to aluminum, carbon (such as graphite), cobalt, copper, gallium, gold, indium, iridium, iron, lead, magnesium, mercury (as an amalgam), nickel, niobium, osmium, palladium, platinum, rhenium, rhodium, selenium, silicon (e.g., doped polycrystalline silicon), silver, tantalum, tin, titanium, tungsten, uranium, vanadium, zinc, zirconium, mixtures thereof, and alloys, oxides, or metallic compounds of these elements.
The processor 204 may be configured to generate and/or process control signals to the various sections of the data processing unit 102 during the operation of the data processing unit 102. In certain embodiments, the processor 204 also includes memory (not shown) for storing data such as the identification information for the data processing unit 102, as well as the data associated with signals received from the sensor 101. The stored information may be retrieved and processed for transmission to the primary receiver unit 104 under the control of the processor 204.
Furthermore, the power supply 207 may include a commercially available battery.
In certain embodiments, a manufacturing process of the data processing unit 102 may place the data processing unit 102 in the lower power, non-operating state (i.e., post-manufacture sleep mode). In this manner, the shelf life of the data processing unit 102 may be significantly improved. Moreover, as shown in FIG.
2, while the power supply unit 207 is shown as coupled to the processor 204, and as such, the processor 204 is configured to provide control of the power supply unit 207, it should be noted that within the scope of the present disclosure, the power supply unit 207 is configured to provide the necessary power to each of the components of the data processing unit 102 shown in FIG. 2.
Referring back to FIG. 2, the power supply section 207 of the data processing unit 102 in one embodiment may include a rechargeable battery unit that may be recharged by a separate power supply recharging unit (for example, provided in the receiver unit 104) so that the data processing unit 102 may be powered for a longer period of usage time. In certain embodiments, the data processing unit 102 may be configured without a battery in the power supply section 207, in which case the data processing unit 102 may be configured to receive power from an external power supply source (for example, a battery, electrical outlet, etc.) as discussed in further detail below.
Referring yet again to FIG. 2, a temperature detection section 203 of the data processing unit 102 is configured to monitor the temperature of the skin near the sensor insertion site. The temperature reading may be used to adjust the analyte readings obtained from the analog interface 201. Also shown is a leak detection circuit 214 coupled to the guard trace (G) 211 and the processor 204 in the data processing unit 102 of the data monitoring and management system 100. The leak detection circuit 214 may be configured to detect leakage current in the sensor 101 to determine whether the measured sensor data are corrupt or whether the measured data from the sensor 101 is accurate. Such detection may trigger a notification to the user.
FIG. 3 shows a block diagram of an embodiment of the receiver/monitor unit, such as the primary receiver unit 104, of the data monitoring and management system shown in FIG. 1. The primary receiver unit 104 includes one or more of. a blood glucose test strip interface 301, an RF receiver 302, an input 303, a temperature monitor section 304, and a clock 305, each of which are operatively coupled to a processing and storage section 307. The primary receiver unit 104 also includes a power supply 306 operatively coupled to a power conversion and monitoring section 308. Further, the power conversion and monitoring section 308 is also coupled to the receiver processing and storage section 307. Moreover, also shown are a receiver serial communication section 309, and an output 310, each operatively coupled to the processing and storage unit 307. The receiver may include user input and/or interface components or may be free of user input and/or interface components.
In certain embodiments, the test strip interface 301 includes a glucose level testing portion to receive a blood (or other body fluid sample) glucose test or information related thereto. For example, the interface may include a test strip port to receive a glucose test strip. The device may determine the glucose level of the test strip, and optionally display (or otherwise notice) the glucose level on the output 310 of the primary receiver unit 104. Any suitable test strip may be employed, e.g., test strips that only require a very small amount (e.g., one microliter or less, e.g., 0.5 microliter or less, e.g., 0.1 microliter or less), of applied sample to the strip in order to obtain accurate glucose information, e.g. Freestyle blood glucose test strips from Abbott Diabetes Care Inc. Glucose information obtained by the in vitro glucose testing device may be used for a variety of purposes, computations, etc. For example, the information may be used to calibrate sensor 101, confirm results of the sensor 101 to increase the confidence thereof (e.g., in instances in which information obtained by sensor 101 is employed in therapy related decisions), etc.
In one aspect, the RF receiver 302 is configured to communicate, via the communication link 103 (FIG. 1) with the RF transmitter 206 of the data processing unit 102, to receive encoded data from the data processing unit 102 for, among others, signal mixing, demodulation, and other data processing. The input 303 of the primary receiver unit 104 is configured to allow the user to enter information into the primary receiver unit 104 as needed. In one aspect, the input 303 may include keys of a keypad, a touch-sensitive screen, and/or a voice-activated input command unit, and the like. The temperature monitor section 304 may be configured to provide temperature information of the primary receiver unit 104 to the processing and control section 307, while the clock 305 provides, among others, real time or clock information to the processing and storage section 307.
Each of the various components of the primary receiver unit 104 shown in FIG. 3 is powered by the power supply 306 (or other power supply) which, in certain embodiments, includes a battery. Furthermore, the power conversion and monitoring section 308 is configured to monitor the power usage by the various components in the primary receiver unit 104 for effective power management and may alert the user, for example, in the event of power usage which renders the primary receiver unit 104 in sub-optimal operating conditions. The serial communication section 309 in the primary receiver unit 104 is configured to provide a bi-directional communication path from the testing and/or manufacturing equipment for, among others, initialization, testing, and configuration of the primary receiver unit 104.
Serial communication section 309 can also be used to upload data to a computer, such as time-stamped blood glucose data. The communication link with an external device (not shown) can be made, for example, by cable (such as USB or serial cable), infrared (IR) or RF link. The output/display 310 of the primary receiver unit 104 is configured to provide, among others, a graphical user interface (GUI), and may include a liquid crystal display (LCD) for displaying information.
Additionally, the output/display 310 may also include an integrated speaker for outputting audible signals as well as to provide vibration output as commonly found in handheld electronic devices, such as mobile telephones, pagers, etc. In certain embodiments, the primary receiver unit 104 also includes an electro-luminescent lamp configured to provide backlighting to the output 310 for output visual display in dark ambient surroundings.
Referring back to FIG. 3, the primary receiver unit 104 may also include a storage section such as a programmable, non-volatile memory device as part of the processing and storage section 307, or provided separately in the primary receiver unit 104, operatively coupled to the processor. The processing and storage section may be configured to perform Manchester decoding (or other protocol(s)) as well as error detection and correction upon the encoded data received from the data processing unit 102 via the communication link 103.
In further embodiments, the data processing unit 102 and/or the primary receiver unit 104 and/or the secondary receiver unit 106, and/or the data processing terminal/infusion section 105 may be configured to receive the blood glucose value wirelessly over a communication link from, for example, a blood glucose meter.
In further embodiments, a user manipulating or using the analyte monitoring system 100 (FIG. 1) may manually input the blood glucose value using, for example, a user interface (for example, a keyboard, keypad, voice commands, and the like) incorporated in the one or more of the data processing unit 102, the primary receiver unit 104, secondary receiver unit 106, or the data processing terminal/infusion section 105.
Additional detailed descriptions are provided in U.S. Patent Nos. 5,262,035;
5,264,104; 5,262,305; 5,320,715; 5,593,852; 6,175,752; 6,650,471; 6,746, 582, and in application No. 10/745,878 filed December 26, 2003 entitled "Continuous Glucose Monitoring System and Methods of Use", each of which is incorporated herein by reference.
FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor in accordance with the present disclosure. The sensor 400 includes electrodes 401, 402 and 403 on a base 404. The sensor may be wholly implantable in a user or may be configured so that only a portion is positioned within (internal) a user and another portion outside (external) a user. For example, the sensor 400 may include a portion positionable above a surface of the skin 410, and a portion positioned below the skin.
In such embodiments, the external portion may include contacts (connected to respective electrodes of the second portion by traces) to connect to another device also external to the user such as a transmitter unit. While the embodiment of FIG. 4 shows three electrodes side-by-side on the same surface of base 404, other configurations are contemplated, e.g., fewer or greater electrodes, some or all electrodes on different surfaces of the base or present on another base, some or all electrodes stacked together, electrodes of differing materials and dimensions, etc.
FIG. 5A shows a perspective view of an embodiment of an electrochemical analyte sensor 500 having a first portion (which in this embodiment may be characterized as a major portion) positionable above a surface of the skin 510, and a second portion (which in this embodiment may be characterized as a minor portion) that includes an insertion tip 530 positionable below the skin, e.g., penetrating through the skin and into, e.g., the subcutaneous space 520, in contact with the user's biofluid such as interstitial fluid. Contact portions of a working electrode 501, a reference electrode 502, and a counter electrode 503 are positioned on the portion of the sensor 500 situated above the skin surface 510. Working electrode 501, a reference electrode 502, and a counter electrode 503 are shown at the second section and particularly at the insertion tip 530. Traces may be provided from the electrode at the tip to the contact, as shown in FIG. 5A. It is to be understood that greater or fewer electrodes may be provided on a sensor. For example, a sensor may include more than one working electrode and/or the counter and reference electrodes may be a single counter/reference electrode, etc.
FIG. 5B shows a cross sectional view of a portion of the sensor 500 of FIG.
5A. The electrodes 501, 502 and 503, of the sensor 500 as well as the substrate and the dielectric layers are provided in a layered configuration or construction.
For example, as shown in FIG. 513, in one aspect, the sensor 500 (such as the sensor unit 101 FIG. 1), includes a substrate layer 504, and a first conducting layer 501 such as carbon, gold, etc., disposed on at least a portion of the substrate layer 504, and which may provide the working electrode. Also shown disposed on at least a portion of the first conducting layer 501 is a sensing layer 508.
Referring back to FIG. 5B, a first insulation layer such as a first dielectric layer 505 is disposed or layered on at least a portion of the first conducting layer 501, and further, a second conducting layer 509 may be disposed or stacked on top of at least a portion of the first insulation layer (or dielectric layer) 505. As shown in FIG.
513, the second conducting layer 509 may provide the reference electrode 502, and in one aspect, may include a layer of silver/silver chloride (Ag/AgCI), gold, etc.
Referring still again to FIG. 513, a second insulation layer 506 such as a dielectric layer in one embodiment may be disposed or layered on at least a portion of the second conducting layer 509. Further, a third conducting layer 503 may provide the counter electrode 503. It may be disposed on at least a portion of the second insulation layer 506. Finally, a third insulation layer 507 may be disposed or layered on at least a portion of the third conducting layer 503. In this manner, the sensor 500 may be layered such that at least a portion of each of the conducting layers is separated by a respective insulation layer (for example, a dielectric layer).
The embodiment of FIGS. 5A and 5B show the layers having different lengths. Some or all of the layers may have the same or different lengths and/or widths.
In certain embodiments, some or all of the electrodes 501, 502, 503 may be provided on the same side of the substrate 504 in the layered construction as described above, or alternatively, may be provided in a co-planar manner such that two or more electrodes may be positioned on the same plane (e.g., side-by side (e.g., parallel) or angled relative to each other) on the substrate 504. For example, co-planar electrodes may include a suitable spacing there between and/or include dielectric material or insulation material disposed between the conducting layers/electrodes.
Furthermore, in certain embodiments one or more of the electrodes 501, 502, 503 may be disposed on opposing sides of the substrate 504. In such embodiments, contact pads may be on the same or different sides of the substrate. For example, an electrode may be on a first side and its respective contact may be on a second side, e.g., a trace connecting the electrode and the contact may traverse through the substrate.
In certain embodiments, the data processing unit 102 may be configured to perform sensor insertion detection and data quality analysis, information pertaining to which may also transmitted to the primary receiver unit 104 periodically at the predetermined time interval. In turn, the receiver unit 104 may be configured to perform, for example, skin temperature compensation/correction as well as calibration of the sensor data received from the data processing unit 102.
As noted above, analyte sensors may include an analyte-responsive enzyme to provide a sensing component or sensing layer. Some analytes, such as oxygen, can be directly electrooxidized or electroreduced on a sensor, and more specifically at least on a working electrode of a sensor. Other analytes, such as glucose and lactate, require the presence of at least one electron transfer agent and/or at least one catalyst to facilitate the electrooxidation or electroreduction of the analyte.
Catalysts may also be used for those analytes, such as oxygen, that can be directly electrooxidized or electroreduced on the working electrode. For these analytes, each working electrode includes a sensing layer (see for example sensing layer 508 of FIG. 513) formed proximate to or on a surface of a working electrode. In many embodiments, a sensing layer is formed near or on only a small portion of at least a working electrode.
A variety of different sensing layer configurations may be used. In certain embodiments, the sensing layer is deposited on the conductive material of a working electrode. The sensing layer may extend beyond the conductive material of the working electrode. In some cases, the sensing layer may also extend over other electrodes, e.g., over the counter electrode and/or reference electrode (or counter/reference is provided). The sensing layer may be integral with the material of an electrode.
A sensing layer that is in direct contact with the working electrode may contain an electron transfer agent to transfer electrons directly or indirectly between the analyte and the working electrode, and/or a catalyst to facilitate a reaction of the analyte. For example, a glucose, lactate, or oxygen electrode may be formed having a sensing layer which contains a catalyst, such as glucose oxidase, lactate oxidase, or laccase, respectively, and an electron transfer agent that facilitates the electrooxidation of the glucose, lactate, or oxygen, respectively.
In one aspect, the RF receiver 302 is configured to communicate, via the communication link 103 (FIG. 1) with the RF transmitter 206 of the data processing unit 102, to receive encoded data from the data processing unit 102 for, among others, signal mixing, demodulation, and other data processing. The input 303 of the primary receiver unit 104 is configured to allow the user to enter information into the primary receiver unit 104 as needed. In one aspect, the input 303 may include keys of a keypad, a touch-sensitive screen, and/or a voice-activated input command unit, and the like. The temperature monitor section 304 may be configured to provide temperature information of the primary receiver unit 104 to the processing and control section 307, while the clock 305 provides, among others, real time or clock information to the processing and storage section 307.
Each of the various components of the primary receiver unit 104 shown in FIG. 3 is powered by the power supply 306 (or other power supply) which, in certain embodiments, includes a battery. Furthermore, the power conversion and monitoring section 308 is configured to monitor the power usage by the various components in the primary receiver unit 104 for effective power management and may alert the user, for example, in the event of power usage which renders the primary receiver unit 104 in sub-optimal operating conditions. The serial communication section 309 in the primary receiver unit 104 is configured to provide a bi-directional communication path from the testing and/or manufacturing equipment for, among others, initialization, testing, and configuration of the primary receiver unit 104.
Serial communication section 309 can also be used to upload data to a computer, such as time-stamped blood glucose data. The communication link with an external device (not shown) can be made, for example, by cable (such as USB or serial cable), infrared (IR) or RF link. The output/display 310 of the primary receiver unit 104 is configured to provide, among others, a graphical user interface (GUI), and may include a liquid crystal display (LCD) for displaying information.
Additionally, the output/display 310 may also include an integrated speaker for outputting audible signals as well as to provide vibration output as commonly found in handheld electronic devices, such as mobile telephones, pagers, etc. In certain embodiments, the primary receiver unit 104 also includes an electro-luminescent lamp configured to provide backlighting to the output 310 for output visual display in dark ambient surroundings.
Referring back to FIG. 3, the primary receiver unit 104 may also include a storage section such as a programmable, non-volatile memory device as part of the processing and storage section 307, or provided separately in the primary receiver unit 104, operatively coupled to the processor. The processing and storage section may be configured to perform Manchester decoding (or other protocol(s)) as well as error detection and correction upon the encoded data received from the data processing unit 102 via the communication link 103.
In further embodiments, the data processing unit 102 and/or the primary receiver unit 104 and/or the secondary receiver unit 106, and/or the data processing terminal/infusion section 105 may be configured to receive the blood glucose value wirelessly over a communication link from, for example, a blood glucose meter.
In further embodiments, a user manipulating or using the analyte monitoring system 100 (FIG. 1) may manually input the blood glucose value using, for example, a user interface (for example, a keyboard, keypad, voice commands, and the like) incorporated in the one or more of the data processing unit 102, the primary receiver unit 104, secondary receiver unit 106, or the data processing terminal/infusion section 105.
Additional detailed descriptions are provided in U.S. Patent Nos. 5,262,035;
5,264,104; 5,262,305; 5,320,715; 5,593,852; 6,175,752; 6,650,471; 6,746, 582, and in application No. 10/745,878 filed December 26, 2003 entitled "Continuous Glucose Monitoring System and Methods of Use", each of which is incorporated herein by reference.
FIG. 4 shows a schematic diagram of an embodiment of an analyte sensor in accordance with the present disclosure. The sensor 400 includes electrodes 401, 402 and 403 on a base 404. The sensor may be wholly implantable in a user or may be configured so that only a portion is positioned within (internal) a user and another portion outside (external) a user. For example, the sensor 400 may include a portion positionable above a surface of the skin 410, and a portion positioned below the skin.
In such embodiments, the external portion may include contacts (connected to respective electrodes of the second portion by traces) to connect to another device also external to the user such as a transmitter unit. While the embodiment of FIG. 4 shows three electrodes side-by-side on the same surface of base 404, other configurations are contemplated, e.g., fewer or greater electrodes, some or all electrodes on different surfaces of the base or present on another base, some or all electrodes stacked together, electrodes of differing materials and dimensions, etc.
FIG. 5A shows a perspective view of an embodiment of an electrochemical analyte sensor 500 having a first portion (which in this embodiment may be characterized as a major portion) positionable above a surface of the skin 510, and a second portion (which in this embodiment may be characterized as a minor portion) that includes an insertion tip 530 positionable below the skin, e.g., penetrating through the skin and into, e.g., the subcutaneous space 520, in contact with the user's biofluid such as interstitial fluid. Contact portions of a working electrode 501, a reference electrode 502, and a counter electrode 503 are positioned on the portion of the sensor 500 situated above the skin surface 510. Working electrode 501, a reference electrode 502, and a counter electrode 503 are shown at the second section and particularly at the insertion tip 530. Traces may be provided from the electrode at the tip to the contact, as shown in FIG. 5A. It is to be understood that greater or fewer electrodes may be provided on a sensor. For example, a sensor may include more than one working electrode and/or the counter and reference electrodes may be a single counter/reference electrode, etc.
FIG. 5B shows a cross sectional view of a portion of the sensor 500 of FIG.
5A. The electrodes 501, 502 and 503, of the sensor 500 as well as the substrate and the dielectric layers are provided in a layered configuration or construction.
For example, as shown in FIG. 513, in one aspect, the sensor 500 (such as the sensor unit 101 FIG. 1), includes a substrate layer 504, and a first conducting layer 501 such as carbon, gold, etc., disposed on at least a portion of the substrate layer 504, and which may provide the working electrode. Also shown disposed on at least a portion of the first conducting layer 501 is a sensing layer 508.
Referring back to FIG. 5B, a first insulation layer such as a first dielectric layer 505 is disposed or layered on at least a portion of the first conducting layer 501, and further, a second conducting layer 509 may be disposed or stacked on top of at least a portion of the first insulation layer (or dielectric layer) 505. As shown in FIG.
513, the second conducting layer 509 may provide the reference electrode 502, and in one aspect, may include a layer of silver/silver chloride (Ag/AgCI), gold, etc.
Referring still again to FIG. 513, a second insulation layer 506 such as a dielectric layer in one embodiment may be disposed or layered on at least a portion of the second conducting layer 509. Further, a third conducting layer 503 may provide the counter electrode 503. It may be disposed on at least a portion of the second insulation layer 506. Finally, a third insulation layer 507 may be disposed or layered on at least a portion of the third conducting layer 503. In this manner, the sensor 500 may be layered such that at least a portion of each of the conducting layers is separated by a respective insulation layer (for example, a dielectric layer).
The embodiment of FIGS. 5A and 5B show the layers having different lengths. Some or all of the layers may have the same or different lengths and/or widths.
In certain embodiments, some or all of the electrodes 501, 502, 503 may be provided on the same side of the substrate 504 in the layered construction as described above, or alternatively, may be provided in a co-planar manner such that two or more electrodes may be positioned on the same plane (e.g., side-by side (e.g., parallel) or angled relative to each other) on the substrate 504. For example, co-planar electrodes may include a suitable spacing there between and/or include dielectric material or insulation material disposed between the conducting layers/electrodes.
Furthermore, in certain embodiments one or more of the electrodes 501, 502, 503 may be disposed on opposing sides of the substrate 504. In such embodiments, contact pads may be on the same or different sides of the substrate. For example, an electrode may be on a first side and its respective contact may be on a second side, e.g., a trace connecting the electrode and the contact may traverse through the substrate.
In certain embodiments, the data processing unit 102 may be configured to perform sensor insertion detection and data quality analysis, information pertaining to which may also transmitted to the primary receiver unit 104 periodically at the predetermined time interval. In turn, the receiver unit 104 may be configured to perform, for example, skin temperature compensation/correction as well as calibration of the sensor data received from the data processing unit 102.
As noted above, analyte sensors may include an analyte-responsive enzyme to provide a sensing component or sensing layer. Some analytes, such as oxygen, can be directly electrooxidized or electroreduced on a sensor, and more specifically at least on a working electrode of a sensor. Other analytes, such as glucose and lactate, require the presence of at least one electron transfer agent and/or at least one catalyst to facilitate the electrooxidation or electroreduction of the analyte.
Catalysts may also be used for those analytes, such as oxygen, that can be directly electrooxidized or electroreduced on the working electrode. For these analytes, each working electrode includes a sensing layer (see for example sensing layer 508 of FIG. 513) formed proximate to or on a surface of a working electrode. In many embodiments, a sensing layer is formed near or on only a small portion of at least a working electrode.
A variety of different sensing layer configurations may be used. In certain embodiments, the sensing layer is deposited on the conductive material of a working electrode. The sensing layer may extend beyond the conductive material of the working electrode. In some cases, the sensing layer may also extend over other electrodes, e.g., over the counter electrode and/or reference electrode (or counter/reference is provided). The sensing layer may be integral with the material of an electrode.
A sensing layer that is in direct contact with the working electrode may contain an electron transfer agent to transfer electrons directly or indirectly between the analyte and the working electrode, and/or a catalyst to facilitate a reaction of the analyte. For example, a glucose, lactate, or oxygen electrode may be formed having a sensing layer which contains a catalyst, such as glucose oxidase, lactate oxidase, or laccase, respectively, and an electron transfer agent that facilitates the electrooxidation of the glucose, lactate, or oxygen, respectively.
In certain embodiments which include more than one working electrode, one or more of the working electrodes do not have a corresponding sensing layer, or have a sensing layer which does not contain one or more components (e.g., an electron transfer agent and/or catalyst) needed to electrolyze the analyte. Thus, the signal at this working electrode corresponds to background signal which may be removed from the analyte signal obtained from one or more other working electrodes that are associated with fully-functional sensing layers by, for example, subtracting the signal.
In certain embodiments, the sensing layer includes one or more electron transfer agents. Electron transfer agents that may be employed are electroreducible and electrooxidizable ions or molecules having redox potentials that are a few hundred millivolts above or below the redox potential of the standard calomel electrode (SCE). The electron transfer agent may be organic, organometallic, or inorganic. Examples of organic redox species are quinones and species that in their oxidized state have quinoid structures, such as Nile blue and indophenol.
Examples of organometallic redox species are metallocenes such as ferrocene. Examples of inorganic redox species are hexacyanoferrate (III), ruthenium hexamine etc.
In certain embodiments, electron transfer agents have structures or charges which prevent or substantially reduce the diffusional loss of the electron transfer agent during the period of time that the sample is being analyzed. For example, electron transfer agents include but are not limited to a redox species, e.g., bound to a polymer which can in turn be disposed on or near the working electrode. The bond between the redox species and the polymer may be covalent, coordinative, or ionic.
Although any organic, organometallic or inorganic redox species may be bound to a polymer and used as an electron transfer agent, in certain embodiments the redox species is a transition metal compound or complex, e.g., osmium, ruthenium, iron, and cobalt compounds or complexes. It will be recognized that many redox species described for use with a polymeric component may also be used, without a polymeric component.
One type of polymeric electron transfer agent contains a redox species covalently bound in a polymeric composition. An example of this type of mediator is poly(vinylferrocene). Another type of electron transfer agent contains an ionically-bound redox species. This type of mediator may include a charged polymer coupled to an oppositely charged redox species. Examples of this type of mediator include a negatively charged polymer coupled to a positively charged redox species such as an osmium or ruthenium polypyridyl cation. Another example of an ionically-bound mediator is a positively charged polymer such as quaternized poly(4-vinyl pyridine) or poly(1-vinyl imidazole) coupled to a negatively charged redox species such as ferricyanide or ferrocyanide. In other embodiments, electron transfer agents include a redox species coordinatively bound to a polymer. For example, the mediator may be formed by coordination of an osmium or cobalt 2,2'-bipyridyl complex to poly(I
-vinyl imidazole) or poly(4-vinyl pyridine).
Suitable electron transfer agents are osmium transition metal complexes with one or more ligands, each ligand having a nitrogen-containing heterocycle such as 2,2'-bipyridine, 1, 1 0-phenanthroline, 1-methyl, 2-pyridyl biimidazole, or derivatives thereof. The electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof. The electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof. One example of an electron transfer agent includes (a) a polymer or copolymer having pyridine or imidazole functional groups and (b) osmium cations complexed with two ligands, each ligand containing 2,2'-bipyridine, 1,10-phenanthroline, or derivatives thereof, the two ligands not necessarily being the same.
Some derivatives of 2,2'-bipyridine for complexation with the osmium cation include but are not limited to 4,4'-dimethyl-2,2'-bipyridine and mono-, di-, and polyalkoxy-2,2'-bipyridines, such as 4,4'-dimethoxy-2,2'-bipyridine. Derivatives of 1,10-phenanthroline for complexation with the osmium cation include but are not limited to 4,7-dimethyl- 1, 1 0-phenanthroline and mono, di-, and polyalkoxy- 1, 10-phenanthrolines, such as 4,7-dimethoxy-1,10-phenanthroline. Polymers for complexation with the osmium cation include but are not limited to polymers and copolymers of poly(1-vinyl imidazole) (referred to as "PVI") and poly(4-vinyl pyridine) (referred to as "PVP"). Suitable copolymer substituents of poly(I -vinyl imidazole) include acrylonitrile, acrylamide, and substituted or quaternized N-vinyl imidazole, e.g., electron transfer agents with osmium complexed to a polymer or copolymer of poly(1-vinyl imidazole).
Embodiments may employ electron transfer agents having a redox potential ranging from about -200 mV to about +200 mV versus the standard calomel electrode (SCE). The sensing layer may also include a catalyst which is capable of catalyzing a reaction of the analyte. The catalyst may also, in some embodiments, act as an electron transfer agent. One example of a suitable catalyst is an enzyme which catalyzes a reaction of the analyte. For example, a catalyst, such as a glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinoline quinone (PQQ) dependent glucose dehydrogenase, flavine adenine dinucleotide (FAD) dependent glucose dehydrogenase, or nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase), may be used when the analyte of interest is glucose. A lactate oxidase or lactate dehydrogenase may be used when the analyte of interest is lactate.
Laccase may be used when the analyte of interest is oxygen or when oxygen is generated or consumed in response to a reaction of the analyte.
In certain embodiments, a catalyst may be attached to a polymer, cross linking the catalyst with another electron transfer agent (which, as described above, may be polymeric. A second catalyst may also be used in certain embodiments. This second catalyst may be used to catalyze a reaction of a product compound resulting from the catalyzed reaction of the analyte. The second catalyst may operate with an electron transfer agent to electrolyze the product compound to generate a signal at the working electrode. Alternatively, a second catalyst may be provided in an interferent-eliminating layer to catalyze reactions that remove interferents.
Certain embodiments include a Wired EnzymeTM sensing layer that works at a gentle oxidizing potential, e.g., a potential of about +40 mV. This sensing layer uses an osmium (Os) -based mediator designed for low potential operation and is stably anchored in a polymeric layer. Accordingly, in certain embodiments the sensing element is redox active component that includes (1) Osmium-based mediator molecules attached by stable (bidente) ligands anchored to a polymeric backbone, and (2) glucose oxidase enzyme molecules. These two constituents are crosslinked together.
A mass transport limiting layer (not shown), e.g., an analyte flux modulating layer, may be included with the sensor to act as a diffusion-limiting barrier to reduce the rate of mass transport of the analyte, for example, glucose or lactate, into the region around the working electrodes. The mass transport limiting layers are useful in limiting the flux of an analyte to a working electrode in an electrochemical sensor so that the sensor is linearly responsive over a large range of analyte concentrations and is easily calibrated. Mass transport limiting layers may include polymers and may be biocompatible. A mass transport limiting layer may serve many functions, e.g., functionalities of a biocompatible layer and/or interferent-eliminating layer may be provided by the mass transport limiting layer.
In certain embodiments, a mass transport limiting layer is a membrane composed of crosslinked polymers containing heterocyclic nitrogen groups, such as polymers of polyvinylpyridine and polyvinylimidazole. Embodiments also include membranes that are made of a polyurethane, or polyether urethane, or chemically related material, or membranes that are made of silicone, and the like.
According certain embodiments, a membrane is formed by crosslinking in situ a polymer, modified with a zwitterionic moiety, a non-pyridine copolymer component, and optionally another moiety that is either hydrophilic or hydrophobic, and/or has other desirable properties, in an alcohol-buffer solution. The modified polymer may be made from a precursor polymer containing heterocyclic nitrogen groups. Optionally, hydrophilic or hydrophobic modifiers may be used to "fine-tune"
the permeability of the resulting membrane to an analyte of interest. Optional hydrophilic modifiers, such as poly(ethylene glycol), hydroxyl or polyhydroxyl modifiers, may be used to enhance the biocompatibility of the polymer or the resulting membrane.
A membrane may be formed in situ by applying an alcohol-buffer solution of a crosslinker and a modified polymer over an enzyme-containing sensing layer and allowing the solution to cure for about one to two days or other appropriate time period. The crosslinker-polymer solution may be applied to the sensing layer by placing a droplet or droplets of the solution on the sensor, by dipping the sensor into the solution, or the like. Generally, the thickness of the membrane is controlled by the concentration of the solution, by the number of droplets of the solution applied, by the number of times the sensor is dipped in the solution, or by any combination of these factors. A membrane applied in this manner may have any combination of the following functions: (1) mass transport limitation, i.e., reduction of the flux of analyte that can reach the sensing layer, (2) biocompatibility enhancement, or (3) interferent reduction.
The electrochemical sensors may employ any suitable measurement technique.
For example, may detect current or may employ potentiometry. Technique may include, but are not limited to amperometry, coulometry, voltammetry. In some embodiments, sensing systems may be optical, colorimetric, and the like.
In certain embodiments, the sensing system detects hydrogen peroxide to infer glucose levels. For example, a hydrogen peroxide-detecting sensor may be constructed in which a sensing layer includes enzyme such as glucose oxides, glucose dehydrogensae, or the like, and is positioned proximate to the working electrode. The sending layer may be covered by a membrane that is selectively permeable to glucose.
Once the glucose passes through the membrane, it is oxidized by the enzyme and reduced glucose oxidase can then be oxidized by reacting with molecular oxygen to produce hydrogen peroxide.
Certain embodiments include a hydrogen peroxide-detecting sensor constructed from a sensing layer prepared by crosslinking two components together, for example: (1) a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE, and (2) periodate oxidized horseradish peroxidase (HRP). Such a sensor functions in a reductive mode; the working electrode is controlled at a potential negative to that of the Os complex, resulting in mediated reduction of hydrogen peroxide through the HRP catalyst.
In another example, a potentiometric sensor can be constructed as follows. A
glucose-sensing layer is constructed by crosslinking together (1) a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials from about -200 mV to +200 mV vs. SCE, and (2) glucose oxidase. This sensor can then be used in a potentiometric mode, by exposing the sensor to a glucose containing solution, under conditions of zero current flow, and allowing the ratio of reduced/oxidized Os to reach an equilibrium value. The reduced/oxidized Os ratio varies in a reproducible way with the glucose concentration, and will cause the electrode's potential to vary in a similar way.
A sensor may also include an active agent such as an anticlotting and/or antiglycolytic agent(s) disposed on at least a portion a sensor that is positioned in a user. An anticlotting agent may reduce or eliminate the clotting of blood or other body fluid around the sensor, particularly after insertion of the sensor. Blood clots may foul the sensor or irreproducibly reduce the amount of analyte which diffuses into the sensor. Examples of useful anticlotting agents include heparin and tissue plasminogen activator (TPA), as well as other known anticlotting agents. Embodiments may include an antiglycolytic agent or precursor thereof. Examples of antiglycolytic agents are glyceraldehyde, fluoride ion, and mannose. The term "antiglycolytic" is used broadly herein to include any substance that at least retards glucose consumption of living cells.
Sensors described herein may be configured to require no system calibration or no user calibration. For example, a sensor may be factory calibrated and need not require further calibrating. In certain embodiments, calibration may be required, but may be done without user intervention, i.e., may be automatic. In those embodiments in which calibration by the user is required, the calibration may be according to a predetermined schedule or may be dynamic, i.e., the time for which may be determined by the system on a real-time basis according to various factors, such as but not limited to glucose concentration and/or temperature and/or rate of change of glucose, etc.
Calibration may be accomplished using an in vitro test strip or other calibrator, e.g., a small sample test strip such as a test strip that requires less than about 1 microliter of sample (for example FreeStyle blood glucose monitoring test strips from Abbott Diabetes Care Inc.). For example, test strips that require less than about 1 nanoliter of sample may be used. In certain embodiments, a sensor may be calibrated using only one sample of body fluid per calibration event. For example, a user need only lance a body part one time to obtain a sample for a calibration event (e.g., for a test strip), or may lance more than one time within a short period of time if an insufficient volume of sample is obtained firstly. Embodiments include obtaining and using multiple samples of body fluid for a given calibration event, where glucose values of each sample are substantially similar. Data obtained from a given calibration event may be used independently to calibrate or combined with data obtained from previous calibration events, e.g., averaged including weighted averaged, etc., to calibrate. In certain embodiments, a system need only be calibrated once by a user, where recalibration of the system is not required.
An analyte system may include an optional alarm system that, e.g., based on information from a processor, warns the patient of a potentially detrimental condition of the analyte. For example, if glucose is the analyte, an alarm system may warn a user of conditions such as hypoglycemia and/or hyperglycemia and/or impending hypoglycemia, and/or impending hyperglycemia. An alarm system may be triggered when analyte levels reach or exceed a threshold value. An alarm system may also, or alternatively, be activated when the rate of change, or acceleration of the rate of change, in analyte level increase or decrease approaches, reaches or exceeds a threshold rate or acceleration. For example, in the case of a glucose monitoring system, an alarm system may be activated if the rate of change in glucose concentration exceeds a threshold value which might indicate that a hyperglycemic or hypoglycemic condition is likely to occur. A system may also include system alarms that notify a user of system information such as battery condition, calibration, sensor dislodgment, sensor malfunction, etc. Alarms may be, for example, auditory and/or visual. Other sensory-stimulating alarm systems may be used including alarm systems which heat, cool, vibrate, or produce a mild electrical shock when activated.
The subject disclosure also includes sensors used in sensor-based drug delivery systems. The system may provide a drug to counteract the high or low level of the analyte in response to the signals from one or more sensors.
Alternatively, the system may monitor the drug concentration to ensure that the drug remains within a desired therapeutic range. The drug delivery system may include one or more (e.g., two or more) sensors, a processing unit such as a transmitter, a receiver/display unit, and a drug administration system. In some cases, some or all components may be integrated in a single unit. The sensor-based drug delivery system may use data from the one or more sensors to provide necessary input for a control algorithm/mechanism to adjust the administration of drugs, e.g., automatically or semi-automatically. As an example, a glucose sensor may be used to control and adjust the administration of insulin from an external or implanted insulin pump.
Returning to the Figures, as discussed above, the sensitivity associated with the analyte sensor may be attenuated during the first 24 hours or so following the sensor insertion due to, for example, tissue trauma, and the like, potentially resulting in ESA condition for the analyte sensor. Accordingly, in accordance with embodiments of the present disclosure, analyte sensor calibration management is provided to effectively detect the occurrence of the sensor ESA condition, properly categorize it and thereafter, manage the ESA condition such that potentially false readings from the sensor are minimized while the time period by which the reporting of the monitored analyte level from the sensor is initiated as close to the initial sensor insertion as possible.
In one aspect, the analyte sensor calibration management routine may be configured to detect the presence of ESA condition, confirm the detected ESA
event, and to manage calibration during the confirmed ESA event to ensure optimal calibration sensitivity estimate.
In one aspect, the analyte sensor calibration management algorithm includes three parts" (1) ESA detection, (2) ESA categorization, and (3) ESA
management.
Each aspect or part of the management algorithm is discussed in detail below.
In one aspect, the ESA detection component of the calibration management algorithm includes detection of the sensor signal (for example, the raw current signal from the analyte sensor) and evaluating it for characteristics of ESA
condition. If ESA condition is detected based on this evaluation, a calibration of the analyte sensor is requested (for example, by prompting the user to perform a fingerstick measurement and enter the resulting reference blood glucose measurement value) to obtain a sensitivity used to confirm the ESA event.
The ESA categorization aspect of the sensor calibration management routine in one aspect of the present disclosure includes rating the severity of the possible attenuation in the analyte sensor signal based on the sensitivities from the calibration measurements. In one aspect, the ESA categorization routine may classify the sensor signal characteristics into one of three categories: (a) No ESA (0), (b) Possible ESA
(1), or (b) Likely ESA (2), based upon which, the ESA management component of the calibration management routine, in one aspect, performs additional processing to, for example, output the resulting monitored analyte level (for example, on the display of the receiver unit 104/106 (FIG. 1), or request additional reference blood glucose measurements within a given time period, to verify that the ESA condition is no longer present or insignificant.
More specifically, the ESA management routine of the calibration management algorithm, in one aspect, may be configured to either update the calibration sensitivity and report or display the monitored analyte level from the sensor, update the calibration sensitivity and temporarily report the monitored analyte level, or suspend reporting of the monitored analyte level, based, at least in part, on the ESA categorization routine. In this manner, in one aspect of the present disclosure, there is provided an effective sensor calibration management approach that optimizes the analyte monitoring system accuracy and improves user experience, based on, for example, maximizing data yield (reporting the monitored glucose level as early as possible from the initial insertion), while minimizing the number of necessary calibration attempts (for example, the need to perform in vitro blood glucose testing).
More specifically, in one aspect, the ESA detection routine of the calibration management algorithm may be configured to detect possible ESA events by evaluating various signal characteristics, including sensor output, temperature, and/or elapsed time from sensor insertion. The ESA detection routine in one aspect evaluates the sensor signal for characteristics similar to those present or associated with ESA events, including, for example a depression or attenuation in the sensor signal during the first 24 hours. The threshold for the ESA detection routine may vary according to apriori knowledge of how the probability of the ESA event may be correlated to other measurable quantities, and/or according to real-time revision of the likelihood of the ESA event itself. An example of apriori knowledge may include the correlation of the probability of the ESA condition to elapsed time since the start of sensor life (i.e., sensor insertion).
When the ESA detection routine determines that there is a high probability that the sensor output is exhibiting ESA condition characteristics, in one aspect, another calibration measurement (i.e., fingerstick test) may be requested to be used to categorize and confirm the ESA event. The calibration request timing and the sensor signal reporting following the ESA condition detection may vary depending on the certainty or the likelihood of the ESA condition presence based on the ESA
detection routine.
For example, in one embodiment, if the ESA detection routine determines that the probability of ESA condition is high, then calibration may be requested immediately (for example, by prompting the user to perform another fingerstick test) and provide the reference blood glucose measurement value obtained, and the sensor data representing the monitored analyte level are not reported to the user, but rather, withheld (for example, by disabling, suspending or deactivating the display in the receiver unit 104/106) until a calibration measurement can be performed to confirm the presence of ESA condition. On the other hand, if the ESA detection routine determines that the likelihood of the presence of ESA condition is less certain, sensor data corresponding to the monitored analyte level may be reported or displayed to the user on a conditional basis, and additional calibrations may be requested at a later scheduled time if the attenuated signal characteristics (potentially indicating a likelihood of ESA condition) persist for a predetermined time period.
The ESA categorization routine of the analyte sensor calibration management algorithm in one aspect, may be configured to categorize the sensor signal characteristics into three levels that are based on the confidence in the existence of ESA condition for the sensor. The routine may be configured to assess the sensor signal by looking at magnitude of the raw sensor signal (Sr), as well as the sensitivity of the sensor signal obtained from a reference glucose measurement, for which both magnitude (Si) and variation (dSi) from previous reference measurements are considered. Thresholds for each signal measurement (Sr, Si and dSi), assigned for each of the three algorithm categorization levels (0, 1 or 2), may be checked to assign the sensitivity to one of the three ESA categories.
The three categories indicate the confidence level or the likelihood that ESA
condition is present for the analyte sensor. For example, No ESA (level 0) indicates that there is no likelihood that ESA condition is present for the sensor.
Possible ESA
(level 1) indicates that there may be a possibility of ESA condition present for the sensor at this calibration event. Further, Likely ESA (level 2) indicates that it is likely there is ESA condition present for the sensor at the current calibration event. The checks for these measurements are performed at each calibration measurement, for example, when the user performs a fingerstick test to provide the reference blood glucose measurement, resulting in the appropriate categorization for each calibration event. Since the probability of the ESA signal characteristic varies with elapsed time from the initiation of sensor wear, the thresholds for the ESA categorization routine may vary over time. The thresholds may also vary based on the outcome of previous calibration measurements for any given sensor, since the probability that a given calibration will result in a detection of ESA increases when a signal perturbation has been previously observed for the sensor.
The ESA management routine of the sensor calibration management algorithm in one aspect of the present disclosure has three outcomes that are based on the level of confidence in the presence of ESA condition for the sensor. For calibrations that are categorized as having No ESA (level 0), it is not likely that an ESA event will result in inaccurate results, and therefore, the sensor data corresponding to the monitored analyte level are determined and reported based on the sensitivity obtained from the calibration event.
For calibrations that are categorized as Possible ESA (level 1), the sensitivity estimate may likely be valid for a limited time period, and therefore, the sensor data corresponding to the monitored analyte level may be determined and reported to the user based on the sensitivity obtained from the calibration event on a probationary basis (for a predetermined time period such as, for example, two hours or any other suitable probationary time period), after which the user may be prompted to perform another calibration to confirm the continued validity of the sensitivity obtained from calibration.
For calibrations categorized as Likely ESA (level 2), it is highly likely that the sensor data corresponding to the monitored analyte level will include substantial attenuation or error, and therefore, the reporting or output of the sensor data is suspended for a predetermined wait period during which the sensor signal is allowed to recover (for example, from the temporary attenuation). At the end of the predetermined wait time period, the user may be requested to perform another fingerstick test to perform another calibration to verify that ESA condition is no longer present or that it is insignificant.
In this manner, in accordance with various embodiments of the present disclosure, analyte sensor calibration management is provided which effectively processes the analyte sensor signals to maximize the accurate reporting of the monitored analyte level while minimizing the potential for providing false or erroneous readings from the sensor during the occurrence of signal attenuation events.
In one aspect of the present disclosure, the routines and algorithms described herein may be incorporated in the receiver unit 104/106, the transmitter unit 102, or the data processing terminal/infusion section 105 of the analyte monitoring system 100 (FIG. 1). More specifically, in accordance with the embodiments of the present disclosure, there may be provided one or more signal detectors configured to perform some, shared or all of the routines described herein to management sensor calibration for the ESA detection, the ESA categorization, and the ESA management, by for example, one or more processors, state machines and the like which may include integrated circuits, application specific integrated circuits (ASIC), and/or combination of hardware and software components including memory devices such as random access memory (RAM), read only memory (ROM), solid state drives, and the like.
More specifically, in one embodiment, a plurality of signal detectors may be used to implement the calibration management routine described herein. A first signal detector may be configured for detection of ESA state based on blood glucose measurements or other reference information and the analyte sensor data from the sensor analyte monitoring system. The outcome of a first signal detector may be configured to determine whether the monitored sensor signal from the analyte monitoring system is in ESA condition.
A second signal detector may be configured to monitor the analyte monitoring system sampled data (for example, one minute data, or any suitable sampling rate). In one aspect, a second signal detector may be configured to instruct the analyte monitoring system to prompt the user to enter an immediate or scheduled blood glucose measurement (for example, based on a fingerstick test using a blood glucose meter) confirm whether an ESA condition exists, and to be used in conjunction with the first signal detector - i.e., the detection of ESA state of the analyte monitoring system based on the reference blood glucose measurements.
In one aspect, the first and second signal detectors are configured to generate one of a plurality, e.g., three, ESA levels - level 0: no ESA, level 1:
possible ESA, and level 2: likely ESA. As discussed above, in one aspect, the level 2 condition associated with possible ESA state of the sensor may be characterized as no significant signal attenuation but based on the detected or monitored conditions associated with the sensor, a verification of the potential ESA condition is desired or necessary within a predetermined period, such as, two hours (or any other suitable time period).
First signal detector and ESA Categorization module The fingerstick test (or reference blood glucose measurement)-based ESA
detector (ESA FS) operates when a calibration attempt passes a data condition verification routine during the active ESA detection phase. More specifically, the ESA_FS detector starts its activity at the first baseline calibration (for example, at about one hour or less from the time of sensor insertion). It remains active during the initial phase of the sensor life (for example, approximately the first 24 hours from initial insertion) when the likelihood of ESA condition is greatest.
In one embodiment, the first signal detector takes the role of "ESA
Categorization" module 620 (FIG. 6) during active ESA condition detection phase. In addition, if other signal detectors do not suspect ESA condition, but an eligible fingerstick blood glucose measurement is made during the active ESA condition detection phase, first signal detector also takes the role of "ESA Detection"
module 610.
The ESA FS detector uses two tests, one relative and one absolute, either of which can detect signal attenuation levels (ESA FS level) based on any reference blood glucose measurement within the active ESA detection phase. The higher of the two levels may be chosen if they are not the same for the two tests. More specifically, in one embodiment, the relative test compares the value of the latest immediate sensitivity based on the latest fingerstick blood glucose test, Si(k), to the values of the previous immediate sensitivity, Si(k-1), and the most recent immediate sensitivity used to calculate the composite sensitivity, Si(m). The values Si(k), Si(k-1), and Si(m) are selected such that calibration post condition verifications pass at those instances (at time index k, k-1, and m). In one aspect, manual calibrations are subject to the tests performed by the ESA_FS detector, but the resulting immediate sensitivities may not be used as previous values.
Based on the relative test, two ratios are formed, Si(k)/Si(k-1), and Si(k)lSi(m).
The two threshold values of ESA_FS levels are assigned using these ratios as follows:
(1) ESA FS level 2 (likely ESA condition) if:
Si(k)/Si(k-1) < Klo_Re1 ESAFS[2] , OR Si(k)/Si(m) < K1oRelESAFS_Cal[2], (2) ESA FS level 1 (possible ESA condition) if NOT ESA_FS level 2 AND:
Si(k)/Si(k-1) < Klo_Re1 ESAFS[1] OR Si(k)/Si(m) < KloRel ESAFS_Cal[1]
where K1o Re1 ESAFS[2] is less than or equal to K1oRel ESAFS[1], and further, K1oRe1ESAFS_Cal[2] is less than or equal to K1oReI ESAFS_Cal[1], and further, where each of these parameters may be predetermined values (for example, set at 0.5 or 0.75 or other suitable value) programmed or programmable in the receiver unit 104/106 (FIG.
1) of the analyte monitoring system, for example.
Otherwise, the relative test of ESA_FS generates a level 0 output indicative of absence of ESA condition.
In accordance with aspects of the present disclosure, the absolute test compares the sensitivity level Si(k) to sensitivity thresholds scaled to the analyte sensor nominal sensitivity Snom. As in the relative test, Sj(k) may be chosen such that it passes calibration post condition verifications. ESA_FS levels are assigned as follows:
ESA-FS level 2 (likely ESA condition) if: Si(k)/Snom < Kmin AbsESAFS[2]
ESA_FS level 1 (possibl ESA condition) if NOT ESA_FS level 2 AND:
Si(k)/ Snom < Kmin Abs ESA FS[1]
where < Kmin_Abs_ESAFS[2] is less tha nequal to Kmin AbsESAFs[1], and further, each of these two parameters may be predetermines or programmed.
Otherwise, the absolute test of ESA_FS generates a level 0 output (indicating no detected ESA condition).
The threshold values for the relative and absolute tests above may be valid when the likelihood of ESA condition is the greatest. When the ESA detectors remain active beyond that time up to an absolute latest time beyond which the ESA
detection will be ignored by the system, the likelihood of ESA may be assumed to be correlated to the elapsed time since sensor insertion, and that different likelihoods allow for different tradeoffs between maximizing ESA detection and minimizing the number of calibration requests.
Second signal detector The second signal detector in the analyte monitoring system is based on inferring ESA condition from the analyte sensor signal characteristics. One example of a signal characteristic is the detection of low glucose values. When this detector reports a nonzero ESA level (for example, presence of signal attenuation (ESA)), there are two possibilities: either the system is in ESA, or the user is in (or near) hypoglycemia.
In one embodiment, the second signal detector may be configured to include the functions of the "ESA Detection" module 610 (FIG. 6), and is not used solely to categorize the detected ESA condition for the "ESA Management" module 630 of the overall system. When the second signal detector produces a nonzero output, a reference blood glucose measurement is expected in a manner determined by the "ESA Management" module 630 of the overall system.
To minimize the effect of noise, a predefined number of the most recent unfiltered glucose samples from the analyte sensor, GCAL, are averaged to derive at the glucose value GESA CGM.
The detector reports one of three possible ESA levels based on the glucose value GESA CGM:
ESA level 2 (likely ESA condition) if: GESAcGM < GminESACGM[2]
ESA level 1 (possible ESA condition) if NOT ESA_FS level 2 AND:
GESACGM < Gmin ESA CGM[1]
where GminESACGM[2] is less than or equal to GminESACGM[1], and further, correspond to predetermined values or parameters programmed into the system.
Otherwise, the absolute test of ESA generates a level 0 output indicating no detected ESA condition. Furthermore, if all of the most recent predefined number of unfiltered glucose sample GCAL is not available, the second signal detector may be configured to report a zero level.
ESA Event Manager In one embodiment, different roles of the first signal detector and the coexistence of the second signal detector may be managed by the "ESA
Management"
module 630 (FIG. 6). The ESA management may be influenced by the sensitivity and specificity of each detector, the history of past or prior calibration events and reference blood glucose measurement timing, the scheduled calibration events in the near future, and other aspects including usability.
In certain embodiments, the sensing layer includes one or more electron transfer agents. Electron transfer agents that may be employed are electroreducible and electrooxidizable ions or molecules having redox potentials that are a few hundred millivolts above or below the redox potential of the standard calomel electrode (SCE). The electron transfer agent may be organic, organometallic, or inorganic. Examples of organic redox species are quinones and species that in their oxidized state have quinoid structures, such as Nile blue and indophenol.
Examples of organometallic redox species are metallocenes such as ferrocene. Examples of inorganic redox species are hexacyanoferrate (III), ruthenium hexamine etc.
In certain embodiments, electron transfer agents have structures or charges which prevent or substantially reduce the diffusional loss of the electron transfer agent during the period of time that the sample is being analyzed. For example, electron transfer agents include but are not limited to a redox species, e.g., bound to a polymer which can in turn be disposed on or near the working electrode. The bond between the redox species and the polymer may be covalent, coordinative, or ionic.
Although any organic, organometallic or inorganic redox species may be bound to a polymer and used as an electron transfer agent, in certain embodiments the redox species is a transition metal compound or complex, e.g., osmium, ruthenium, iron, and cobalt compounds or complexes. It will be recognized that many redox species described for use with a polymeric component may also be used, without a polymeric component.
One type of polymeric electron transfer agent contains a redox species covalently bound in a polymeric composition. An example of this type of mediator is poly(vinylferrocene). Another type of electron transfer agent contains an ionically-bound redox species. This type of mediator may include a charged polymer coupled to an oppositely charged redox species. Examples of this type of mediator include a negatively charged polymer coupled to a positively charged redox species such as an osmium or ruthenium polypyridyl cation. Another example of an ionically-bound mediator is a positively charged polymer such as quaternized poly(4-vinyl pyridine) or poly(1-vinyl imidazole) coupled to a negatively charged redox species such as ferricyanide or ferrocyanide. In other embodiments, electron transfer agents include a redox species coordinatively bound to a polymer. For example, the mediator may be formed by coordination of an osmium or cobalt 2,2'-bipyridyl complex to poly(I
-vinyl imidazole) or poly(4-vinyl pyridine).
Suitable electron transfer agents are osmium transition metal complexes with one or more ligands, each ligand having a nitrogen-containing heterocycle such as 2,2'-bipyridine, 1, 1 0-phenanthroline, 1-methyl, 2-pyridyl biimidazole, or derivatives thereof. The electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof. The electron transfer agents may also have one or more ligands covalently bound in a polymer, each ligand having at least one nitrogen-containing heterocycle, such as pyridine, imidazole, or derivatives thereof. One example of an electron transfer agent includes (a) a polymer or copolymer having pyridine or imidazole functional groups and (b) osmium cations complexed with two ligands, each ligand containing 2,2'-bipyridine, 1,10-phenanthroline, or derivatives thereof, the two ligands not necessarily being the same.
Some derivatives of 2,2'-bipyridine for complexation with the osmium cation include but are not limited to 4,4'-dimethyl-2,2'-bipyridine and mono-, di-, and polyalkoxy-2,2'-bipyridines, such as 4,4'-dimethoxy-2,2'-bipyridine. Derivatives of 1,10-phenanthroline for complexation with the osmium cation include but are not limited to 4,7-dimethyl- 1, 1 0-phenanthroline and mono, di-, and polyalkoxy- 1, 10-phenanthrolines, such as 4,7-dimethoxy-1,10-phenanthroline. Polymers for complexation with the osmium cation include but are not limited to polymers and copolymers of poly(1-vinyl imidazole) (referred to as "PVI") and poly(4-vinyl pyridine) (referred to as "PVP"). Suitable copolymer substituents of poly(I -vinyl imidazole) include acrylonitrile, acrylamide, and substituted or quaternized N-vinyl imidazole, e.g., electron transfer agents with osmium complexed to a polymer or copolymer of poly(1-vinyl imidazole).
Embodiments may employ electron transfer agents having a redox potential ranging from about -200 mV to about +200 mV versus the standard calomel electrode (SCE). The sensing layer may also include a catalyst which is capable of catalyzing a reaction of the analyte. The catalyst may also, in some embodiments, act as an electron transfer agent. One example of a suitable catalyst is an enzyme which catalyzes a reaction of the analyte. For example, a catalyst, such as a glucose oxidase, glucose dehydrogenase (e.g., pyrroloquinoline quinone (PQQ) dependent glucose dehydrogenase, flavine adenine dinucleotide (FAD) dependent glucose dehydrogenase, or nicotinamide adenine dinucleotide (NAD) dependent glucose dehydrogenase), may be used when the analyte of interest is glucose. A lactate oxidase or lactate dehydrogenase may be used when the analyte of interest is lactate.
Laccase may be used when the analyte of interest is oxygen or when oxygen is generated or consumed in response to a reaction of the analyte.
In certain embodiments, a catalyst may be attached to a polymer, cross linking the catalyst with another electron transfer agent (which, as described above, may be polymeric. A second catalyst may also be used in certain embodiments. This second catalyst may be used to catalyze a reaction of a product compound resulting from the catalyzed reaction of the analyte. The second catalyst may operate with an electron transfer agent to electrolyze the product compound to generate a signal at the working electrode. Alternatively, a second catalyst may be provided in an interferent-eliminating layer to catalyze reactions that remove interferents.
Certain embodiments include a Wired EnzymeTM sensing layer that works at a gentle oxidizing potential, e.g., a potential of about +40 mV. This sensing layer uses an osmium (Os) -based mediator designed for low potential operation and is stably anchored in a polymeric layer. Accordingly, in certain embodiments the sensing element is redox active component that includes (1) Osmium-based mediator molecules attached by stable (bidente) ligands anchored to a polymeric backbone, and (2) glucose oxidase enzyme molecules. These two constituents are crosslinked together.
A mass transport limiting layer (not shown), e.g., an analyte flux modulating layer, may be included with the sensor to act as a diffusion-limiting barrier to reduce the rate of mass transport of the analyte, for example, glucose or lactate, into the region around the working electrodes. The mass transport limiting layers are useful in limiting the flux of an analyte to a working electrode in an electrochemical sensor so that the sensor is linearly responsive over a large range of analyte concentrations and is easily calibrated. Mass transport limiting layers may include polymers and may be biocompatible. A mass transport limiting layer may serve many functions, e.g., functionalities of a biocompatible layer and/or interferent-eliminating layer may be provided by the mass transport limiting layer.
In certain embodiments, a mass transport limiting layer is a membrane composed of crosslinked polymers containing heterocyclic nitrogen groups, such as polymers of polyvinylpyridine and polyvinylimidazole. Embodiments also include membranes that are made of a polyurethane, or polyether urethane, or chemically related material, or membranes that are made of silicone, and the like.
According certain embodiments, a membrane is formed by crosslinking in situ a polymer, modified with a zwitterionic moiety, a non-pyridine copolymer component, and optionally another moiety that is either hydrophilic or hydrophobic, and/or has other desirable properties, in an alcohol-buffer solution. The modified polymer may be made from a precursor polymer containing heterocyclic nitrogen groups. Optionally, hydrophilic or hydrophobic modifiers may be used to "fine-tune"
the permeability of the resulting membrane to an analyte of interest. Optional hydrophilic modifiers, such as poly(ethylene glycol), hydroxyl or polyhydroxyl modifiers, may be used to enhance the biocompatibility of the polymer or the resulting membrane.
A membrane may be formed in situ by applying an alcohol-buffer solution of a crosslinker and a modified polymer over an enzyme-containing sensing layer and allowing the solution to cure for about one to two days or other appropriate time period. The crosslinker-polymer solution may be applied to the sensing layer by placing a droplet or droplets of the solution on the sensor, by dipping the sensor into the solution, or the like. Generally, the thickness of the membrane is controlled by the concentration of the solution, by the number of droplets of the solution applied, by the number of times the sensor is dipped in the solution, or by any combination of these factors. A membrane applied in this manner may have any combination of the following functions: (1) mass transport limitation, i.e., reduction of the flux of analyte that can reach the sensing layer, (2) biocompatibility enhancement, or (3) interferent reduction.
The electrochemical sensors may employ any suitable measurement technique.
For example, may detect current or may employ potentiometry. Technique may include, but are not limited to amperometry, coulometry, voltammetry. In some embodiments, sensing systems may be optical, colorimetric, and the like.
In certain embodiments, the sensing system detects hydrogen peroxide to infer glucose levels. For example, a hydrogen peroxide-detecting sensor may be constructed in which a sensing layer includes enzyme such as glucose oxides, glucose dehydrogensae, or the like, and is positioned proximate to the working electrode. The sending layer may be covered by a membrane that is selectively permeable to glucose.
Once the glucose passes through the membrane, it is oxidized by the enzyme and reduced glucose oxidase can then be oxidized by reacting with molecular oxygen to produce hydrogen peroxide.
Certain embodiments include a hydrogen peroxide-detecting sensor constructed from a sensing layer prepared by crosslinking two components together, for example: (1) a redox compound such as a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials of about +200 mV vs. SCE, and (2) periodate oxidized horseradish peroxidase (HRP). Such a sensor functions in a reductive mode; the working electrode is controlled at a potential negative to that of the Os complex, resulting in mediated reduction of hydrogen peroxide through the HRP catalyst.
In another example, a potentiometric sensor can be constructed as follows. A
glucose-sensing layer is constructed by crosslinking together (1) a redox polymer containing pendent Os polypyridyl complexes with oxidation potentials from about -200 mV to +200 mV vs. SCE, and (2) glucose oxidase. This sensor can then be used in a potentiometric mode, by exposing the sensor to a glucose containing solution, under conditions of zero current flow, and allowing the ratio of reduced/oxidized Os to reach an equilibrium value. The reduced/oxidized Os ratio varies in a reproducible way with the glucose concentration, and will cause the electrode's potential to vary in a similar way.
A sensor may also include an active agent such as an anticlotting and/or antiglycolytic agent(s) disposed on at least a portion a sensor that is positioned in a user. An anticlotting agent may reduce or eliminate the clotting of blood or other body fluid around the sensor, particularly after insertion of the sensor. Blood clots may foul the sensor or irreproducibly reduce the amount of analyte which diffuses into the sensor. Examples of useful anticlotting agents include heparin and tissue plasminogen activator (TPA), as well as other known anticlotting agents. Embodiments may include an antiglycolytic agent or precursor thereof. Examples of antiglycolytic agents are glyceraldehyde, fluoride ion, and mannose. The term "antiglycolytic" is used broadly herein to include any substance that at least retards glucose consumption of living cells.
Sensors described herein may be configured to require no system calibration or no user calibration. For example, a sensor may be factory calibrated and need not require further calibrating. In certain embodiments, calibration may be required, but may be done without user intervention, i.e., may be automatic. In those embodiments in which calibration by the user is required, the calibration may be according to a predetermined schedule or may be dynamic, i.e., the time for which may be determined by the system on a real-time basis according to various factors, such as but not limited to glucose concentration and/or temperature and/or rate of change of glucose, etc.
Calibration may be accomplished using an in vitro test strip or other calibrator, e.g., a small sample test strip such as a test strip that requires less than about 1 microliter of sample (for example FreeStyle blood glucose monitoring test strips from Abbott Diabetes Care Inc.). For example, test strips that require less than about 1 nanoliter of sample may be used. In certain embodiments, a sensor may be calibrated using only one sample of body fluid per calibration event. For example, a user need only lance a body part one time to obtain a sample for a calibration event (e.g., for a test strip), or may lance more than one time within a short period of time if an insufficient volume of sample is obtained firstly. Embodiments include obtaining and using multiple samples of body fluid for a given calibration event, where glucose values of each sample are substantially similar. Data obtained from a given calibration event may be used independently to calibrate or combined with data obtained from previous calibration events, e.g., averaged including weighted averaged, etc., to calibrate. In certain embodiments, a system need only be calibrated once by a user, where recalibration of the system is not required.
An analyte system may include an optional alarm system that, e.g., based on information from a processor, warns the patient of a potentially detrimental condition of the analyte. For example, if glucose is the analyte, an alarm system may warn a user of conditions such as hypoglycemia and/or hyperglycemia and/or impending hypoglycemia, and/or impending hyperglycemia. An alarm system may be triggered when analyte levels reach or exceed a threshold value. An alarm system may also, or alternatively, be activated when the rate of change, or acceleration of the rate of change, in analyte level increase or decrease approaches, reaches or exceeds a threshold rate or acceleration. For example, in the case of a glucose monitoring system, an alarm system may be activated if the rate of change in glucose concentration exceeds a threshold value which might indicate that a hyperglycemic or hypoglycemic condition is likely to occur. A system may also include system alarms that notify a user of system information such as battery condition, calibration, sensor dislodgment, sensor malfunction, etc. Alarms may be, for example, auditory and/or visual. Other sensory-stimulating alarm systems may be used including alarm systems which heat, cool, vibrate, or produce a mild electrical shock when activated.
The subject disclosure also includes sensors used in sensor-based drug delivery systems. The system may provide a drug to counteract the high or low level of the analyte in response to the signals from one or more sensors.
Alternatively, the system may monitor the drug concentration to ensure that the drug remains within a desired therapeutic range. The drug delivery system may include one or more (e.g., two or more) sensors, a processing unit such as a transmitter, a receiver/display unit, and a drug administration system. In some cases, some or all components may be integrated in a single unit. The sensor-based drug delivery system may use data from the one or more sensors to provide necessary input for a control algorithm/mechanism to adjust the administration of drugs, e.g., automatically or semi-automatically. As an example, a glucose sensor may be used to control and adjust the administration of insulin from an external or implanted insulin pump.
Returning to the Figures, as discussed above, the sensitivity associated with the analyte sensor may be attenuated during the first 24 hours or so following the sensor insertion due to, for example, tissue trauma, and the like, potentially resulting in ESA condition for the analyte sensor. Accordingly, in accordance with embodiments of the present disclosure, analyte sensor calibration management is provided to effectively detect the occurrence of the sensor ESA condition, properly categorize it and thereafter, manage the ESA condition such that potentially false readings from the sensor are minimized while the time period by which the reporting of the monitored analyte level from the sensor is initiated as close to the initial sensor insertion as possible.
In one aspect, the analyte sensor calibration management routine may be configured to detect the presence of ESA condition, confirm the detected ESA
event, and to manage calibration during the confirmed ESA event to ensure optimal calibration sensitivity estimate.
In one aspect, the analyte sensor calibration management algorithm includes three parts" (1) ESA detection, (2) ESA categorization, and (3) ESA
management.
Each aspect or part of the management algorithm is discussed in detail below.
In one aspect, the ESA detection component of the calibration management algorithm includes detection of the sensor signal (for example, the raw current signal from the analyte sensor) and evaluating it for characteristics of ESA
condition. If ESA condition is detected based on this evaluation, a calibration of the analyte sensor is requested (for example, by prompting the user to perform a fingerstick measurement and enter the resulting reference blood glucose measurement value) to obtain a sensitivity used to confirm the ESA event.
The ESA categorization aspect of the sensor calibration management routine in one aspect of the present disclosure includes rating the severity of the possible attenuation in the analyte sensor signal based on the sensitivities from the calibration measurements. In one aspect, the ESA categorization routine may classify the sensor signal characteristics into one of three categories: (a) No ESA (0), (b) Possible ESA
(1), or (b) Likely ESA (2), based upon which, the ESA management component of the calibration management routine, in one aspect, performs additional processing to, for example, output the resulting monitored analyte level (for example, on the display of the receiver unit 104/106 (FIG. 1), or request additional reference blood glucose measurements within a given time period, to verify that the ESA condition is no longer present or insignificant.
More specifically, the ESA management routine of the calibration management algorithm, in one aspect, may be configured to either update the calibration sensitivity and report or display the monitored analyte level from the sensor, update the calibration sensitivity and temporarily report the monitored analyte level, or suspend reporting of the monitored analyte level, based, at least in part, on the ESA categorization routine. In this manner, in one aspect of the present disclosure, there is provided an effective sensor calibration management approach that optimizes the analyte monitoring system accuracy and improves user experience, based on, for example, maximizing data yield (reporting the monitored glucose level as early as possible from the initial insertion), while minimizing the number of necessary calibration attempts (for example, the need to perform in vitro blood glucose testing).
More specifically, in one aspect, the ESA detection routine of the calibration management algorithm may be configured to detect possible ESA events by evaluating various signal characteristics, including sensor output, temperature, and/or elapsed time from sensor insertion. The ESA detection routine in one aspect evaluates the sensor signal for characteristics similar to those present or associated with ESA events, including, for example a depression or attenuation in the sensor signal during the first 24 hours. The threshold for the ESA detection routine may vary according to apriori knowledge of how the probability of the ESA event may be correlated to other measurable quantities, and/or according to real-time revision of the likelihood of the ESA event itself. An example of apriori knowledge may include the correlation of the probability of the ESA condition to elapsed time since the start of sensor life (i.e., sensor insertion).
When the ESA detection routine determines that there is a high probability that the sensor output is exhibiting ESA condition characteristics, in one aspect, another calibration measurement (i.e., fingerstick test) may be requested to be used to categorize and confirm the ESA event. The calibration request timing and the sensor signal reporting following the ESA condition detection may vary depending on the certainty or the likelihood of the ESA condition presence based on the ESA
detection routine.
For example, in one embodiment, if the ESA detection routine determines that the probability of ESA condition is high, then calibration may be requested immediately (for example, by prompting the user to perform another fingerstick test) and provide the reference blood glucose measurement value obtained, and the sensor data representing the monitored analyte level are not reported to the user, but rather, withheld (for example, by disabling, suspending or deactivating the display in the receiver unit 104/106) until a calibration measurement can be performed to confirm the presence of ESA condition. On the other hand, if the ESA detection routine determines that the likelihood of the presence of ESA condition is less certain, sensor data corresponding to the monitored analyte level may be reported or displayed to the user on a conditional basis, and additional calibrations may be requested at a later scheduled time if the attenuated signal characteristics (potentially indicating a likelihood of ESA condition) persist for a predetermined time period.
The ESA categorization routine of the analyte sensor calibration management algorithm in one aspect, may be configured to categorize the sensor signal characteristics into three levels that are based on the confidence in the existence of ESA condition for the sensor. The routine may be configured to assess the sensor signal by looking at magnitude of the raw sensor signal (Sr), as well as the sensitivity of the sensor signal obtained from a reference glucose measurement, for which both magnitude (Si) and variation (dSi) from previous reference measurements are considered. Thresholds for each signal measurement (Sr, Si and dSi), assigned for each of the three algorithm categorization levels (0, 1 or 2), may be checked to assign the sensitivity to one of the three ESA categories.
The three categories indicate the confidence level or the likelihood that ESA
condition is present for the analyte sensor. For example, No ESA (level 0) indicates that there is no likelihood that ESA condition is present for the sensor.
Possible ESA
(level 1) indicates that there may be a possibility of ESA condition present for the sensor at this calibration event. Further, Likely ESA (level 2) indicates that it is likely there is ESA condition present for the sensor at the current calibration event. The checks for these measurements are performed at each calibration measurement, for example, when the user performs a fingerstick test to provide the reference blood glucose measurement, resulting in the appropriate categorization for each calibration event. Since the probability of the ESA signal characteristic varies with elapsed time from the initiation of sensor wear, the thresholds for the ESA categorization routine may vary over time. The thresholds may also vary based on the outcome of previous calibration measurements for any given sensor, since the probability that a given calibration will result in a detection of ESA increases when a signal perturbation has been previously observed for the sensor.
The ESA management routine of the sensor calibration management algorithm in one aspect of the present disclosure has three outcomes that are based on the level of confidence in the presence of ESA condition for the sensor. For calibrations that are categorized as having No ESA (level 0), it is not likely that an ESA event will result in inaccurate results, and therefore, the sensor data corresponding to the monitored analyte level are determined and reported based on the sensitivity obtained from the calibration event.
For calibrations that are categorized as Possible ESA (level 1), the sensitivity estimate may likely be valid for a limited time period, and therefore, the sensor data corresponding to the monitored analyte level may be determined and reported to the user based on the sensitivity obtained from the calibration event on a probationary basis (for a predetermined time period such as, for example, two hours or any other suitable probationary time period), after which the user may be prompted to perform another calibration to confirm the continued validity of the sensitivity obtained from calibration.
For calibrations categorized as Likely ESA (level 2), it is highly likely that the sensor data corresponding to the monitored analyte level will include substantial attenuation or error, and therefore, the reporting or output of the sensor data is suspended for a predetermined wait period during which the sensor signal is allowed to recover (for example, from the temporary attenuation). At the end of the predetermined wait time period, the user may be requested to perform another fingerstick test to perform another calibration to verify that ESA condition is no longer present or that it is insignificant.
In this manner, in accordance with various embodiments of the present disclosure, analyte sensor calibration management is provided which effectively processes the analyte sensor signals to maximize the accurate reporting of the monitored analyte level while minimizing the potential for providing false or erroneous readings from the sensor during the occurrence of signal attenuation events.
In one aspect of the present disclosure, the routines and algorithms described herein may be incorporated in the receiver unit 104/106, the transmitter unit 102, or the data processing terminal/infusion section 105 of the analyte monitoring system 100 (FIG. 1). More specifically, in accordance with the embodiments of the present disclosure, there may be provided one or more signal detectors configured to perform some, shared or all of the routines described herein to management sensor calibration for the ESA detection, the ESA categorization, and the ESA management, by for example, one or more processors, state machines and the like which may include integrated circuits, application specific integrated circuits (ASIC), and/or combination of hardware and software components including memory devices such as random access memory (RAM), read only memory (ROM), solid state drives, and the like.
More specifically, in one embodiment, a plurality of signal detectors may be used to implement the calibration management routine described herein. A first signal detector may be configured for detection of ESA state based on blood glucose measurements or other reference information and the analyte sensor data from the sensor analyte monitoring system. The outcome of a first signal detector may be configured to determine whether the monitored sensor signal from the analyte monitoring system is in ESA condition.
A second signal detector may be configured to monitor the analyte monitoring system sampled data (for example, one minute data, or any suitable sampling rate). In one aspect, a second signal detector may be configured to instruct the analyte monitoring system to prompt the user to enter an immediate or scheduled blood glucose measurement (for example, based on a fingerstick test using a blood glucose meter) confirm whether an ESA condition exists, and to be used in conjunction with the first signal detector - i.e., the detection of ESA state of the analyte monitoring system based on the reference blood glucose measurements.
In one aspect, the first and second signal detectors are configured to generate one of a plurality, e.g., three, ESA levels - level 0: no ESA, level 1:
possible ESA, and level 2: likely ESA. As discussed above, in one aspect, the level 2 condition associated with possible ESA state of the sensor may be characterized as no significant signal attenuation but based on the detected or monitored conditions associated with the sensor, a verification of the potential ESA condition is desired or necessary within a predetermined period, such as, two hours (or any other suitable time period).
First signal detector and ESA Categorization module The fingerstick test (or reference blood glucose measurement)-based ESA
detector (ESA FS) operates when a calibration attempt passes a data condition verification routine during the active ESA detection phase. More specifically, the ESA_FS detector starts its activity at the first baseline calibration (for example, at about one hour or less from the time of sensor insertion). It remains active during the initial phase of the sensor life (for example, approximately the first 24 hours from initial insertion) when the likelihood of ESA condition is greatest.
In one embodiment, the first signal detector takes the role of "ESA
Categorization" module 620 (FIG. 6) during active ESA condition detection phase. In addition, if other signal detectors do not suspect ESA condition, but an eligible fingerstick blood glucose measurement is made during the active ESA condition detection phase, first signal detector also takes the role of "ESA Detection"
module 610.
The ESA FS detector uses two tests, one relative and one absolute, either of which can detect signal attenuation levels (ESA FS level) based on any reference blood glucose measurement within the active ESA detection phase. The higher of the two levels may be chosen if they are not the same for the two tests. More specifically, in one embodiment, the relative test compares the value of the latest immediate sensitivity based on the latest fingerstick blood glucose test, Si(k), to the values of the previous immediate sensitivity, Si(k-1), and the most recent immediate sensitivity used to calculate the composite sensitivity, Si(m). The values Si(k), Si(k-1), and Si(m) are selected such that calibration post condition verifications pass at those instances (at time index k, k-1, and m). In one aspect, manual calibrations are subject to the tests performed by the ESA_FS detector, but the resulting immediate sensitivities may not be used as previous values.
Based on the relative test, two ratios are formed, Si(k)/Si(k-1), and Si(k)lSi(m).
The two threshold values of ESA_FS levels are assigned using these ratios as follows:
(1) ESA FS level 2 (likely ESA condition) if:
Si(k)/Si(k-1) < Klo_Re1 ESAFS[2] , OR Si(k)/Si(m) < K1oRelESAFS_Cal[2], (2) ESA FS level 1 (possible ESA condition) if NOT ESA_FS level 2 AND:
Si(k)/Si(k-1) < Klo_Re1 ESAFS[1] OR Si(k)/Si(m) < KloRel ESAFS_Cal[1]
where K1o Re1 ESAFS[2] is less than or equal to K1oRel ESAFS[1], and further, K1oRe1ESAFS_Cal[2] is less than or equal to K1oReI ESAFS_Cal[1], and further, where each of these parameters may be predetermined values (for example, set at 0.5 or 0.75 or other suitable value) programmed or programmable in the receiver unit 104/106 (FIG.
1) of the analyte monitoring system, for example.
Otherwise, the relative test of ESA_FS generates a level 0 output indicative of absence of ESA condition.
In accordance with aspects of the present disclosure, the absolute test compares the sensitivity level Si(k) to sensitivity thresholds scaled to the analyte sensor nominal sensitivity Snom. As in the relative test, Sj(k) may be chosen such that it passes calibration post condition verifications. ESA_FS levels are assigned as follows:
ESA-FS level 2 (likely ESA condition) if: Si(k)/Snom < Kmin AbsESAFS[2]
ESA_FS level 1 (possibl ESA condition) if NOT ESA_FS level 2 AND:
Si(k)/ Snom < Kmin Abs ESA FS[1]
where < Kmin_Abs_ESAFS[2] is less tha nequal to Kmin AbsESAFs[1], and further, each of these two parameters may be predetermines or programmed.
Otherwise, the absolute test of ESA_FS generates a level 0 output (indicating no detected ESA condition).
The threshold values for the relative and absolute tests above may be valid when the likelihood of ESA condition is the greatest. When the ESA detectors remain active beyond that time up to an absolute latest time beyond which the ESA
detection will be ignored by the system, the likelihood of ESA may be assumed to be correlated to the elapsed time since sensor insertion, and that different likelihoods allow for different tradeoffs between maximizing ESA detection and minimizing the number of calibration requests.
Second signal detector The second signal detector in the analyte monitoring system is based on inferring ESA condition from the analyte sensor signal characteristics. One example of a signal characteristic is the detection of low glucose values. When this detector reports a nonzero ESA level (for example, presence of signal attenuation (ESA)), there are two possibilities: either the system is in ESA, or the user is in (or near) hypoglycemia.
In one embodiment, the second signal detector may be configured to include the functions of the "ESA Detection" module 610 (FIG. 6), and is not used solely to categorize the detected ESA condition for the "ESA Management" module 630 of the overall system. When the second signal detector produces a nonzero output, a reference blood glucose measurement is expected in a manner determined by the "ESA Management" module 630 of the overall system.
To minimize the effect of noise, a predefined number of the most recent unfiltered glucose samples from the analyte sensor, GCAL, are averaged to derive at the glucose value GESA CGM.
The detector reports one of three possible ESA levels based on the glucose value GESA CGM:
ESA level 2 (likely ESA condition) if: GESAcGM < GminESACGM[2]
ESA level 1 (possible ESA condition) if NOT ESA_FS level 2 AND:
GESACGM < Gmin ESA CGM[1]
where GminESACGM[2] is less than or equal to GminESACGM[1], and further, correspond to predetermined values or parameters programmed into the system.
Otherwise, the absolute test of ESA generates a level 0 output indicating no detected ESA condition. Furthermore, if all of the most recent predefined number of unfiltered glucose sample GCAL is not available, the second signal detector may be configured to report a zero level.
ESA Event Manager In one embodiment, different roles of the first signal detector and the coexistence of the second signal detector may be managed by the "ESA
Management"
module 630 (FIG. 6). The ESA management may be influenced by the sensitivity and specificity of each detector, the history of past or prior calibration events and reference blood glucose measurement timing, the scheduled calibration events in the near future, and other aspects including usability.
In the case where the sensor is in the level 0 condition indicating absence of ESA condition, the second signal detector may be configured to begin to operate after the second baseline calibration (that is, the second scheduled calibration time period for the analyte sensor) which may be a floating calibration event (measured from when the no ESA condition is determined) scheduled following the first absolute calibration (measured from the initial sensor insertion event) and thereby reporting measured glucose levels to the user. In one aspect, the display or output of the measured glucose levels may be suspended at a predetermined time associated with the earliest allowable termination of the signal detectors in the system.
In order to avoid closely spaced fingerstick blood glucose measurements, in one aspect, the output from the second signal detector may be ignored when either less than a predefined idle time period has elapsed after a successful baseline calibration where asynchronous stability request is not allowed (for example, minutes) after any calibration attempt, or when less than a predefined idle time period has elapsed prior to the next scheduled baseline calibration where asynchronous stability request is not allowed (for example, 30 minutes) before any scheduled calibration attempt.
In one aspect, during active ESA detection phase, the first signal detector is used to determine whether ESA condition is present or absent. In one embodiment, it is assumed that ESA condition is absent at the sensor start - that is, when the sensor is initially inserted. The transition, behavior, and retention of the states in one aspect are described below. For example, in one aspect, transition into a determination that ESA condition is present occurs when the latest ESA_FS level is determined to be greater than the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation. For example, in the case where level 0 and level 1 are considered not sufficiently stringent for attenuation mitigation, in one aspect of the present disclosure, only level 2 may be configured to trigger the transition to a state where it is determined that ESA condition is present.
When the analyte monitoring system determines that the sensor is in ESA
condition, in one aspect, the receiver unit 104/106 (FIG. 1) may be configured to disable the output or display of the measured or detected glucose level.
Moreover, the receiver unit 104/106 may be configured to maintain the disabled (or suspended or deactivated) output/display for a predefined idle time period after the presence of ESA
condition has been confirmed by the reference blood glucose measurement before the user is prompted for another confirmation (for example, by requesting another fingerstick test) before transitioning to the state with confirmed no ESA
condition.
Furthermore, in yet another aspect, receiver unit 104/106 may be configured to not request a stability calibration verification while sensor is in ESA
condition.
However, any user-motivated or self- initiated fingerstick blood glucose measurement may be used, if confirmed, to transition into a state where ESA condition is absent.
Also, when the sensor is deemed to be in the confirmed no ESA condition, the second signal detector shows a level 0 (reflecting a no ESA condition), and signal precondition verification passes, the receiver unit 104/106 (FIG. 1) of the analyte monitoring system may be configured to request a reference blood glucose measurement to confirm that the absence of ESA condition is complete and/or to initiate calibration.
In one aspect, transition into a state associated with absence of ESA
condition occurs when a new fingerstick blood glucose measurement shows an ESA_FS level (for example, the output of the first signal detector discussed above) that is less than or equal to the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation. A successful calibration is required for glucose results to be reported or displayed, for example.
When it is determined that ESA condition is absent, the sensor signals, in one aspect may be further processed to determine stability and possible errors.
For example, in one aspect, when a level 2 output (i.e., likely ESA condition) from the second signal detector occurs for the first time, an immediate request for a stability calibration may be generated. After the first occurrence of level 2 output from the second signal detector, the analyte sensor signals are checked at the time intervals (for example, approximately 1 to 2 hours, or other suitable time interval) since the last reference blood glucose measurement with stability verification routine before another measurement is requested, after the most recent successful calibration.
Further, a nonzero level (i.e., a level 1 or level 2 - possible or likely ESA
condition) triggers a stability calibration request. Also, in one aspect, if a previous ESA_FS
level is greater than 0, a reference blood glucose measurement is requested at a time interval since the last blood glucose measurement, and ESA_FS is determined using the new reference measurement.
Referring now to the Figures, FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure. As shown, analyte sensor calibration management system in accordance with one aspect of the present disclosure includes an ESA detection module 610, and ESA categorization module 620, and an ESA management module.
As discussed above, the ESA detection module 610 is configured to detect the occurrence of an early signal attenuation event during the initial time period following the analyte sensor insertion or wear, for example, the first 24 hour period measured from the initial sensor insertion.
When signal attenuation associated with an analyte sensor is detected, the ESA
categorization module in one embodiment is configured to properly categorize the detected signal attenuation condition. Thereafter, depending upon the type of ESA
condition detected - for example, no ESA condition detection, likely ESA
condition detection, or possible ESA condition detection, the ESA management module 630 is configured to initiate one or more processes to confirm the detected and categorized signal attenuation condition. And further, to perform additional processing to effectively manage the calibration algorithm associated with the analyte sensor operation such that maximum reportable data yield may be attained, providing improved usability of the analyte sensor for continuously or intermittently monitoring and outputting monitored analyte level such as the fluctuation in the glucose level of a patient or a user.
FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure.
Referring to FIG. 7, the ESA detection routine executed by the ESA detection module 610 (FIG.
6), for example, is described. More specifically, for each monitored signal from the analyte sensor (such as for each one minute data from the analyte sensor), a new timestep is initiated (701), and it is determined whether ESA detector should be or has started (702). If it is determined that the ESA detector has not or should not be started, then the routine waits for the next time step (714) based on the next signal received from the sensor (for example, the subsequent one minute signal received from the analyte sensor).
In order to avoid closely spaced fingerstick blood glucose measurements, in one aspect, the output from the second signal detector may be ignored when either less than a predefined idle time period has elapsed after a successful baseline calibration where asynchronous stability request is not allowed (for example, minutes) after any calibration attempt, or when less than a predefined idle time period has elapsed prior to the next scheduled baseline calibration where asynchronous stability request is not allowed (for example, 30 minutes) before any scheduled calibration attempt.
In one aspect, during active ESA detection phase, the first signal detector is used to determine whether ESA condition is present or absent. In one embodiment, it is assumed that ESA condition is absent at the sensor start - that is, when the sensor is initially inserted. The transition, behavior, and retention of the states in one aspect are described below. For example, in one aspect, transition into a determination that ESA condition is present occurs when the latest ESA_FS level is determined to be greater than the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation. For example, in the case where level 0 and level 1 are considered not sufficiently stringent for attenuation mitigation, in one aspect of the present disclosure, only level 2 may be configured to trigger the transition to a state where it is determined that ESA condition is present.
When the analyte monitoring system determines that the sensor is in ESA
condition, in one aspect, the receiver unit 104/106 (FIG. 1) may be configured to disable the output or display of the measured or detected glucose level.
Moreover, the receiver unit 104/106 may be configured to maintain the disabled (or suspended or deactivated) output/display for a predefined idle time period after the presence of ESA
condition has been confirmed by the reference blood glucose measurement before the user is prompted for another confirmation (for example, by requesting another fingerstick test) before transitioning to the state with confirmed no ESA
condition.
Furthermore, in yet another aspect, receiver unit 104/106 may be configured to not request a stability calibration verification while sensor is in ESA
condition.
However, any user-motivated or self- initiated fingerstick blood glucose measurement may be used, if confirmed, to transition into a state where ESA condition is absent.
Also, when the sensor is deemed to be in the confirmed no ESA condition, the second signal detector shows a level 0 (reflecting a no ESA condition), and signal precondition verification passes, the receiver unit 104/106 (FIG. 1) of the analyte monitoring system may be configured to request a reference blood glucose measurement to confirm that the absence of ESA condition is complete and/or to initiate calibration.
In one aspect, transition into a state associated with absence of ESA
condition occurs when a new fingerstick blood glucose measurement shows an ESA_FS level (for example, the output of the first signal detector discussed above) that is less than or equal to the largest allowable output level from the first signal detector of prior measurements that is considered as an indication of being free from early signal attenuation. A successful calibration is required for glucose results to be reported or displayed, for example.
When it is determined that ESA condition is absent, the sensor signals, in one aspect may be further processed to determine stability and possible errors.
For example, in one aspect, when a level 2 output (i.e., likely ESA condition) from the second signal detector occurs for the first time, an immediate request for a stability calibration may be generated. After the first occurrence of level 2 output from the second signal detector, the analyte sensor signals are checked at the time intervals (for example, approximately 1 to 2 hours, or other suitable time interval) since the last reference blood glucose measurement with stability verification routine before another measurement is requested, after the most recent successful calibration.
Further, a nonzero level (i.e., a level 1 or level 2 - possible or likely ESA
condition) triggers a stability calibration request. Also, in one aspect, if a previous ESA_FS
level is greater than 0, a reference blood glucose measurement is requested at a time interval since the last blood glucose measurement, and ESA_FS is determined using the new reference measurement.
Referring now to the Figures, FIG. 6 is a flowchart illustrating an overall analyte sensor calibration management in accordance with one embodiment of the present disclosure. As shown, analyte sensor calibration management system in accordance with one aspect of the present disclosure includes an ESA detection module 610, and ESA categorization module 620, and an ESA management module.
As discussed above, the ESA detection module 610 is configured to detect the occurrence of an early signal attenuation event during the initial time period following the analyte sensor insertion or wear, for example, the first 24 hour period measured from the initial sensor insertion.
When signal attenuation associated with an analyte sensor is detected, the ESA
categorization module in one embodiment is configured to properly categorize the detected signal attenuation condition. Thereafter, depending upon the type of ESA
condition detected - for example, no ESA condition detection, likely ESA
condition detection, or possible ESA condition detection, the ESA management module 630 is configured to initiate one or more processes to confirm the detected and categorized signal attenuation condition. And further, to perform additional processing to effectively manage the calibration algorithm associated with the analyte sensor operation such that maximum reportable data yield may be attained, providing improved usability of the analyte sensor for continuously or intermittently monitoring and outputting monitored analyte level such as the fluctuation in the glucose level of a patient or a user.
FIG. 7 is a flowchart illustrating early signal attenuation (ESA) detection routine of FIG. 6 in accordance with one aspect of the present disclosure.
Referring to FIG. 7, the ESA detection routine executed by the ESA detection module 610 (FIG.
6), for example, is described. More specifically, for each monitored signal from the analyte sensor (such as for each one minute data from the analyte sensor), a new timestep is initiated (701), and it is determined whether ESA detector should be or has started (702). If it is determined that the ESA detector has not or should not be started, then the routine waits for the next time step (714) based on the next signal received from the sensor (for example, the subsequent one minute signal received from the analyte sensor).
Referring to FIG. 7, if it is determined that ESA detector should or did start (702), then it is determined whether it should be terminated (703). If it is determined that the ESA detector should be terminated (703), then the routine ends (704).
However, if it is determined that the ESA detector should not terminate (703), then it is determined whether a pending reference blood glucose measurement request timer has been activated (705). If it is determined that the pending reference blood glucose measurement request timer has been activated (705), then in one embodiment, a reference blood glucose measurement request is generated and output to the user with a nonzero grace period (706). Thereafter, the ESA detector is suspended and the system awaits for the requested reference blood glucose measurement.
On the other hand, if it is determined that the pending reference blood glucose measurement request timer is not activated (705), then analyte sensor signal information as well as other relevant information is retrieved or obtained (707). That is, for example, the sensor raw current signal, the associated temperature information, sensor counter voltage data, for example, are obtained, in addition to other relevant information such as, for example, the sensor code sensitivity, immediate sensitivity, time duration elapsed since the sensor insertion, and time elapsed since the prior sensor calibration event, for example. Within the scope of the present disclosure, other relevant data related to the operation and characteristics of the analyte sensor may be obtained.
Referring still to FIG. 7, thereafter, the probability or ESA condition presence is determined (709), the result of which is compared to one or more threshold values to determine whether high ESA condition probability exists (710). If it is determined that high ESA condition probability exists, then reference blood glucose measurement data is requested with a nonzero grace period (711), and the ESA detection routine is suspended to await for the requested reference blood glucose measurement data.
On the other hand, if it is determined that high ESA condition probability does not exist (710), then it is determined whether medium ESA condition probability exists (712).
If it is determined that medium ESA condition probably does not exist, then the routine proceeds to wait for the next sensor data (714). On the other hand, if it is determined that medium ESA condition probability exists (712), then a pending reference blood glucose measurement timer is set to activate at a predetermined relative time in the future, unless a successful calibration event is detected prior to the expiration of the activated timer (713).
In the manner described above, in one embodiment of the present disclosure, the ESA detection module 610 (FIG. 6) may be configured to detect attenuation in analyte sensor signal during the initial time period from the sensor insertion.
Referring back to the Figures, FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure. As described in detail above, upon detection of a signal attenuation occurrence associated with an analyte sensor, the detected attenuation is categorized by, for example, the ESA categorization module (620). More specifically, referring now to FIG. 8, for each new timestep associated with the detection of the one minute sensor signal from the analyte sensor, for example (810), it is determined whether ESA detector is active (820). If it is determined that the ESA
detector is not active (or the ESA routine is not activated or initiated), then the ESA
categorization routine terminates (821).
On the other hand, if it is determined that the ESA detector is active (820), then it is determined whether a new reference blood glucose measurement is available (830). If the reference blood glucose measurement is not available, then the routine terminates and waits for the next analyte sensor signal (860). If it is determined, however, that the reference blood glucose measurement is available (830), then analyte sensor related information is retrieved and/or collected (840). In one embodiment, analyte sensor related information may include, for example, sensor signal history, previous reference blood glucose measurement values, calibration time period, and the like. Thereafter, the detected signal attenuation is categorized into one of three categories - level 0, level 1, and level 2, corresponding to no ESA
condition, possible ESA condition, and likely ESA condition, respectively (850) and as discussed in detail above. In one embodiment, after categorization, the routine proceeds to the ESA management module (630) (FIG. 6) and also, repeats the same categorization procedure for the next received sensor signal.
Referring back, as discussed, after performing ESA condition categorization (620) (FIG. 6), in one aspect, the ESA condition management routine is initiated (630). More specifically, FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure. As shown, for each analyte sensor signal received or detected (901), it is first determined whether the ESA detector is active (902). If it is determined that the ESA detector is not active, then the ESA management routine terminates (903).
On the other hand, if it is determined that the ESA detector is active, then it is determined whether a grace period of an existing reference blood glucose measurement request has expired (904). If it is determined that the grace period of the existing reference blood glucose measurement request has expired, then the display or reporting module associated with the output of the analyte sensor data is disabled, suspended, deactivated or otherwise blanked such that no real time glucose information is provided to the user (910). If it is determined however, that the grace period of the existing reference blood glucose measurement request has not expired, then the ESA categorization module output from the ESA categorization module (620) is retrieved (905).
Referring again to FIG. 9, it is thereafter determined whether the ESA
categorization result or output exists (906). If not, then the output or reporting of the real time glucose information proceeds and the user is provided with the glucose level data (914), and thereafter waits to receive the next analyte signal associated with the next timestep (918). On the other hand, if the ESA categorization result exists (906), then it is determined whether the ESA categorization is associated with the current analyte signal (associated with the current timestep, for example) (907). If it is not associated with the current analyte signal, then the routine proceeds to displaying or outputting the monitored analyte level to the user (914), and waits to receive the next analyte signal associated with the next timestep (918).
However, if it is determined that the ESA categorization is associated with the current timestep (907), then it is determined whether the ESA condition categorization is associated with level 2 category indicating a likely ESA condition for the sensor. If it is determined that the ESA condition categorization is associated with level 2 category, then a timer (T_Confirm timer) is started (909) and the reporting or output of the glucose data is disabled (910). If it is determined however, that the ESA
condition category is not associated with level 2, then it is determined whether the categorized ESA condition is level 1 (911). If it is determined to be level 1 indicating a possible ESA condition, then a request for a blood glucose measurement is scheduled for a predetermined time period (T_Cal_U) with a nonzero grace period (912), and the real time glucose information is displayed or output to the user (914).
Referring back to Fig. 9, if it is determined that the ESA condition is not associated with a level 1 category (911), then the calibration for the analyte sensor is updated (913), and the monitored glucose level is displayed or output to the user (914), and the routine waits to receive the next analyte sensor signal (918).
Referring still back to FIG. 9, after the display or output of the glucose value is disabled or blanked (910), it is determined whether the T_Confirm timer was started and the timer expired (915). If it has not expired, the routine waits to receive the next analyte signal (918). If, however, it is determined that the timer (T_Confirm) has lapsed (915), then it is determined whether the characteristics of the sensor is suitable, for example, for calibration (916). If it is determined that the sensor condition is not suitable (916), then the routine waits to receive the next analyte sensor signal (918). On the other hand, if it is determined that the sensor condition is stable (916), then a reference blood glucose measurement is requested with a zero grace period (917).
In the manner described above, in accordance with the various embodiments of the present disclosure, method, apparatus and system for providing effective analyte sensor calibration management is described that monitors the early attenuation of sensor signals and processes the monitored signals to maximize the sensor data yield by providing as much of the useful and accurate monitored glucose level information to the user.
Results from Preliminary Studies A preliminary study, was conducted with 48 sensor insertions in normal (N=10), T1DM (N=1) and T2DM (N=2) subjects using finger stick glucose measurements as a reference. Little deterioration of the results was observed when comparing the mean absolute relative difference (MARD) for the first 10 hours compared to the remaining 10 to 24 hours of day one of sensor use: 13.8% (12.8 -14.9 95% CI) versus 12.6% (11.6 - 13.6 95% Cl) respectively. During the first ten hours 7.5 hours 2.2 hours (average SD) of glucose data would be available to the user substantially maximizing available data yield providing reportable glucose information shortly after the sensor insertion/
However, if it is determined that the ESA detector should not terminate (703), then it is determined whether a pending reference blood glucose measurement request timer has been activated (705). If it is determined that the pending reference blood glucose measurement request timer has been activated (705), then in one embodiment, a reference blood glucose measurement request is generated and output to the user with a nonzero grace period (706). Thereafter, the ESA detector is suspended and the system awaits for the requested reference blood glucose measurement.
On the other hand, if it is determined that the pending reference blood glucose measurement request timer is not activated (705), then analyte sensor signal information as well as other relevant information is retrieved or obtained (707). That is, for example, the sensor raw current signal, the associated temperature information, sensor counter voltage data, for example, are obtained, in addition to other relevant information such as, for example, the sensor code sensitivity, immediate sensitivity, time duration elapsed since the sensor insertion, and time elapsed since the prior sensor calibration event, for example. Within the scope of the present disclosure, other relevant data related to the operation and characteristics of the analyte sensor may be obtained.
Referring still to FIG. 7, thereafter, the probability or ESA condition presence is determined (709), the result of which is compared to one or more threshold values to determine whether high ESA condition probability exists (710). If it is determined that high ESA condition probability exists, then reference blood glucose measurement data is requested with a nonzero grace period (711), and the ESA detection routine is suspended to await for the requested reference blood glucose measurement data.
On the other hand, if it is determined that high ESA condition probability does not exist (710), then it is determined whether medium ESA condition probability exists (712).
If it is determined that medium ESA condition probably does not exist, then the routine proceeds to wait for the next sensor data (714). On the other hand, if it is determined that medium ESA condition probability exists (712), then a pending reference blood glucose measurement timer is set to activate at a predetermined relative time in the future, unless a successful calibration event is detected prior to the expiration of the activated timer (713).
In the manner described above, in one embodiment of the present disclosure, the ESA detection module 610 (FIG. 6) may be configured to detect attenuation in analyte sensor signal during the initial time period from the sensor insertion.
Referring back to the Figures, FIG. 8 is a flowchart illustrating early signal attenuation (ESA) categorization routine of FIG. 6 in accordance with one aspect of the present disclosure. As described in detail above, upon detection of a signal attenuation occurrence associated with an analyte sensor, the detected attenuation is categorized by, for example, the ESA categorization module (620). More specifically, referring now to FIG. 8, for each new timestep associated with the detection of the one minute sensor signal from the analyte sensor, for example (810), it is determined whether ESA detector is active (820). If it is determined that the ESA
detector is not active (or the ESA routine is not activated or initiated), then the ESA
categorization routine terminates (821).
On the other hand, if it is determined that the ESA detector is active (820), then it is determined whether a new reference blood glucose measurement is available (830). If the reference blood glucose measurement is not available, then the routine terminates and waits for the next analyte sensor signal (860). If it is determined, however, that the reference blood glucose measurement is available (830), then analyte sensor related information is retrieved and/or collected (840). In one embodiment, analyte sensor related information may include, for example, sensor signal history, previous reference blood glucose measurement values, calibration time period, and the like. Thereafter, the detected signal attenuation is categorized into one of three categories - level 0, level 1, and level 2, corresponding to no ESA
condition, possible ESA condition, and likely ESA condition, respectively (850) and as discussed in detail above. In one embodiment, after categorization, the routine proceeds to the ESA management module (630) (FIG. 6) and also, repeats the same categorization procedure for the next received sensor signal.
Referring back, as discussed, after performing ESA condition categorization (620) (FIG. 6), in one aspect, the ESA condition management routine is initiated (630). More specifically, FIG. 9 is a flowchart illustrating early signal attenuation (ESA) management routine of FIG. 6 in accordance with one aspect of the present disclosure. As shown, for each analyte sensor signal received or detected (901), it is first determined whether the ESA detector is active (902). If it is determined that the ESA detector is not active, then the ESA management routine terminates (903).
On the other hand, if it is determined that the ESA detector is active, then it is determined whether a grace period of an existing reference blood glucose measurement request has expired (904). If it is determined that the grace period of the existing reference blood glucose measurement request has expired, then the display or reporting module associated with the output of the analyte sensor data is disabled, suspended, deactivated or otherwise blanked such that no real time glucose information is provided to the user (910). If it is determined however, that the grace period of the existing reference blood glucose measurement request has not expired, then the ESA categorization module output from the ESA categorization module (620) is retrieved (905).
Referring again to FIG. 9, it is thereafter determined whether the ESA
categorization result or output exists (906). If not, then the output or reporting of the real time glucose information proceeds and the user is provided with the glucose level data (914), and thereafter waits to receive the next analyte signal associated with the next timestep (918). On the other hand, if the ESA categorization result exists (906), then it is determined whether the ESA categorization is associated with the current analyte signal (associated with the current timestep, for example) (907). If it is not associated with the current analyte signal, then the routine proceeds to displaying or outputting the monitored analyte level to the user (914), and waits to receive the next analyte signal associated with the next timestep (918).
However, if it is determined that the ESA categorization is associated with the current timestep (907), then it is determined whether the ESA condition categorization is associated with level 2 category indicating a likely ESA condition for the sensor. If it is determined that the ESA condition categorization is associated with level 2 category, then a timer (T_Confirm timer) is started (909) and the reporting or output of the glucose data is disabled (910). If it is determined however, that the ESA
condition category is not associated with level 2, then it is determined whether the categorized ESA condition is level 1 (911). If it is determined to be level 1 indicating a possible ESA condition, then a request for a blood glucose measurement is scheduled for a predetermined time period (T_Cal_U) with a nonzero grace period (912), and the real time glucose information is displayed or output to the user (914).
Referring back to Fig. 9, if it is determined that the ESA condition is not associated with a level 1 category (911), then the calibration for the analyte sensor is updated (913), and the monitored glucose level is displayed or output to the user (914), and the routine waits to receive the next analyte sensor signal (918).
Referring still back to FIG. 9, after the display or output of the glucose value is disabled or blanked (910), it is determined whether the T_Confirm timer was started and the timer expired (915). If it has not expired, the routine waits to receive the next analyte signal (918). If, however, it is determined that the timer (T_Confirm) has lapsed (915), then it is determined whether the characteristics of the sensor is suitable, for example, for calibration (916). If it is determined that the sensor condition is not suitable (916), then the routine waits to receive the next analyte sensor signal (918). On the other hand, if it is determined that the sensor condition is stable (916), then a reference blood glucose measurement is requested with a zero grace period (917).
In the manner described above, in accordance with the various embodiments of the present disclosure, method, apparatus and system for providing effective analyte sensor calibration management is described that monitors the early attenuation of sensor signals and processes the monitored signals to maximize the sensor data yield by providing as much of the useful and accurate monitored glucose level information to the user.
Results from Preliminary Studies A preliminary study, was conducted with 48 sensor insertions in normal (N=10), T1DM (N=1) and T2DM (N=2) subjects using finger stick glucose measurements as a reference. Little deterioration of the results was observed when comparing the mean absolute relative difference (MARD) for the first 10 hours compared to the remaining 10 to 24 hours of day one of sensor use: 13.8% (12.8 -14.9 95% CI) versus 12.6% (11.6 - 13.6 95% Cl) respectively. During the first ten hours 7.5 hours 2.2 hours (average SD) of glucose data would be available to the user substantially maximizing available data yield providing reportable glucose information shortly after the sensor insertion/
A second preliminary study included evaluation of the performance of the system described above which included two locations each with 47 subjects (aged 19-66) who wore 2 sensors (abdomen/arm). Continuous glucose readings were collected at one minute intervals from 1 hour after sensor insertion. Venous blood glucose measurements were obtained using a standard laboratory reference (YSI 2300) every minutes for 26 hours across two in-clinic visits during the 5 day sensor wear.
Capillary BG measurements were taken by each subject (on average 20 per day) on a separate blood glucose meter.
The mean and median absolute relative difference between the sensor system 10 and YSI was 14.5% and 10.7% respectively. Moreover, continuous Glucose-Error Grid Analysis combining rate and point information gave 93.9% accurate readings and an additional 3.2% benign errors.
Traditional Clarke Error Grid (CEG) Zone A performance was 77.1% (6229/8084).
This included periods of hypoglycemia and high rates of change of blood glucose 15 during IV insulin challenges. When the rate of change of blood glucose was within 1 mg/dL/min, the Zone A performance was 82.0% (4672/5699). Performance remained constant over all five days, with 80.7% of data in Zone A on day 1 and 74.1 %
in Zone A on day 5 (p=0.4503). Furthermore, Clarke Error Grid Zone A performance compared to capillary blood glucose measurement was 81.2% (3337/4108).
Hypoglycemic events at 70 mg/dL (n=119) were detected by threshold or projected alarm (30 minute setting) 91.6% of the time. Hyperglycemic events at mg/dL (n=144) were detected by threshold or projected alarm 97.2% of the time.
The threshold or projected alarm false alarm rate was 25.2% at 70 mg/dL and 21.2%
at 240 mg/dL.
Based on the foregoing, the results from the second preliminary study demonstrate good performance of the FreeStyle Navigator Continuous Glucose Monitoring System with data displayed from approximately one hour after sensor insertion over five days of sensor wear.
In the manner described above, in accordance with the various embodiments of the present disclosure, the analyte sensor calibration management minimizes the presentation of erroneous analyte sensor results due to ESA conditions, while maximizing reportable analyte sensor data for sensors that do not exhibit the ESA
Capillary BG measurements were taken by each subject (on average 20 per day) on a separate blood glucose meter.
The mean and median absolute relative difference between the sensor system 10 and YSI was 14.5% and 10.7% respectively. Moreover, continuous Glucose-Error Grid Analysis combining rate and point information gave 93.9% accurate readings and an additional 3.2% benign errors.
Traditional Clarke Error Grid (CEG) Zone A performance was 77.1% (6229/8084).
This included periods of hypoglycemia and high rates of change of blood glucose 15 during IV insulin challenges. When the rate of change of blood glucose was within 1 mg/dL/min, the Zone A performance was 82.0% (4672/5699). Performance remained constant over all five days, with 80.7% of data in Zone A on day 1 and 74.1 %
in Zone A on day 5 (p=0.4503). Furthermore, Clarke Error Grid Zone A performance compared to capillary blood glucose measurement was 81.2% (3337/4108).
Hypoglycemic events at 70 mg/dL (n=119) were detected by threshold or projected alarm (30 minute setting) 91.6% of the time. Hyperglycemic events at mg/dL (n=144) were detected by threshold or projected alarm 97.2% of the time.
The threshold or projected alarm false alarm rate was 25.2% at 70 mg/dL and 21.2%
at 240 mg/dL.
Based on the foregoing, the results from the second preliminary study demonstrate good performance of the FreeStyle Navigator Continuous Glucose Monitoring System with data displayed from approximately one hour after sensor insertion over five days of sensor wear.
In the manner described above, in accordance with the various embodiments of the present disclosure, the analyte sensor calibration management minimizes the presentation of erroneous analyte sensor results due to ESA conditions, while maximizing reportable analyte sensor data for sensors that do not exhibit the ESA
signal characteristic. Accordingly, in aspects of the present disclosure, the calibration management algorithm applies to any subcutaneously positioned analyte sensor which may exhibit ESA signal characteristics, and enables the management of calibration during periods when the analyte sensor sensitivity may deviate from the actual sensor sensitivity.
Accordingly, a method in one aspect includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
The predefined time period may include less than approximately one hour.
In another aspect, the method may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
Further, the predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
Also, reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
The various processes described above including the processes performed by the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105 (FIG. 1) in the software application execution environment in the analyte monitoring system 100 including the processes and routines described in conjunction with FIGS. 6-9, may be embodied as computer programs developed using an object oriented language that allows the modeling of complex systems with modular objects to create abstractions that are representative of real world, physical objects and their interrelationships. The software required to carry out the inventive process, which may be stored in the memory or storage device (not shown) of the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105, may be developed by a person of ordinary skill in the art and may include one or more computer program products.
One embodiment of the present disclosure may include positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
The signal from the analyte sensor may be associated with a monitored analyte level.
The detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
The predetermined time period may not exceed approximately 24 hours.
Categorizing the detected analyte sensor signal attenuation may be based at least in part on a predetermined plurality of signal attenuation conditions.
In one aspect, the plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
Another aspect may include outputting data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
Outputting data associated with the monitored analyte level may include outputting data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
The preset time period may not exceed approximately two hours.
One aspect may include requesting a reference blood glucose measurement during the preset time period.
Another aspect may include calibrating the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
Yet another aspect, may include disabling outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
Another embodiment, wherein performing signal processing may include requesting a reference data, and determining a sensitivity value associated with the analyte sensor based on the reference data.
The reference data may include an in vitro blood glucose measurement data.
Accordingly, a method in one aspect includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
The predefined time period may include less than approximately one hour.
In another aspect, the method may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
Further, the predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
Also, reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
The various processes described above including the processes performed by the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105 (FIG. 1) in the software application execution environment in the analyte monitoring system 100 including the processes and routines described in conjunction with FIGS. 6-9, may be embodied as computer programs developed using an object oriented language that allows the modeling of complex systems with modular objects to create abstractions that are representative of real world, physical objects and their interrelationships. The software required to carry out the inventive process, which may be stored in the memory or storage device (not shown) of the data processing unit 102, receiver unit 104/106 or the data processing terminal/infusion section 105, may be developed by a person of ordinary skill in the art and may include one or more computer program products.
One embodiment of the present disclosure may include positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
The signal from the analyte sensor may be associated with a monitored analyte level.
The detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
The predetermined time period may not exceed approximately 24 hours.
Categorizing the detected analyte sensor signal attenuation may be based at least in part on a predetermined plurality of signal attenuation conditions.
In one aspect, the plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
Another aspect may include outputting data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
Outputting data associated with the monitored analyte level may include outputting data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
The preset time period may not exceed approximately two hours.
One aspect may include requesting a reference blood glucose measurement during the preset time period.
Another aspect may include calibrating the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
Yet another aspect, may include disabling outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
Another embodiment, wherein performing signal processing may include requesting a reference data, and determining a sensitivity value associated with the analyte sensor based on the reference data.
The reference data may include an in vitro blood glucose measurement data.
One aspect may include calibrating the analyte sensor based at least in part on the determined sensitivity value.
A further embodiment of the present disclosure includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
The predefined time period may be less than approximately one hour.
Another aspect may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
The predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
Reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
Yet still another aspect of the present disclosure includes inserting at least a portion of a glucose sensor beneath a skin surface of an individual, analyzing glucose-related signal from the sensor to determine sensor stability, and reporting glucose related information to the individual only when it is determined that the sensor is stable, wherein the glucose related information is not reported prior to determination that the sensor is stable.
Sensor stability may be determined using reference data.
Reference data may comprise sampling blood of the individual.
Reference data may be obtained from a glucose test strip.
One aspect may include analyzing the sensor signal to determine whether there exists a decrease in sensor signal.
The analyte sensor may report the glucose related information in about one hour following the insertion.
An apparatus in accordance with still another aspect may include a data communication interface, one or more processors operatively coupled to the data communication interface, and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to position an analyte sensor in fluid contact with an analyte, detect an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorize the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and perform signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
The signal from the analyte sensor may be associated with a monitored analyte level.
The detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
The predetermined time period may not exceed approximately 24 hours.
In one aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to categorize the detected analyte sensor signal attenuation based at least in part on a predetermined plurality of signal attenuation conditions.
The plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
In another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
In yet another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
Furthermore, the preset time period may not exceed approximately two hours.
Moreover, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to request a reference blood glucose measurement during the preset time period.
Further, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to calibrate the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
A further embodiment of the present disclosure includes monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period, and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
The predefined time period may be less than approximately one hour.
Another aspect may include receiving a blood glucose measurement, and calibrating the analyte sensor based on the received blood glucose measurement.
The predetermined threshold may be associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
Reporting the analyte level may include one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
Yet still another aspect of the present disclosure includes inserting at least a portion of a glucose sensor beneath a skin surface of an individual, analyzing glucose-related signal from the sensor to determine sensor stability, and reporting glucose related information to the individual only when it is determined that the sensor is stable, wherein the glucose related information is not reported prior to determination that the sensor is stable.
Sensor stability may be determined using reference data.
Reference data may comprise sampling blood of the individual.
Reference data may be obtained from a glucose test strip.
One aspect may include analyzing the sensor signal to determine whether there exists a decrease in sensor signal.
The analyte sensor may report the glucose related information in about one hour following the insertion.
An apparatus in accordance with still another aspect may include a data communication interface, one or more processors operatively coupled to the data communication interface, and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to position an analyte sensor in fluid contact with an analyte, detect an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorize the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and perform signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
The signal from the analyte sensor may be associated with a monitored analyte level.
The detected attenuation in the signal from the analyte sensor may be associated with an early signal attenuation condition.
The predetermined time period may not exceed approximately 24 hours.
In one aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to categorize the detected analyte sensor signal attenuation based at least in part on a predetermined plurality of signal attenuation conditions.
The plurality of signal attenuation conditions may include a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
In another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
In yet another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to output data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
Furthermore, the preset time period may not exceed approximately two hours.
Moreover, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to request a reference blood glucose measurement during the preset time period.
Further, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to calibrate the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
Moreover, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to disable the outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
In another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to request a reference data, and determine a sensitivity value associated with the analyte sensor based on the reference data.
Reference data may include an in vitro blood glucose measurement data.
Further, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to calibrate the analyte sensor based at least in part on the determined sensitivity value.
Moreover, in still another aspect, there is provided one or more storage devices having processor readable code embodied thereon, said processor readable code for programming one or more processors to estimate an analyte level may comprise, positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
Various other modifications and alterations in the structure and method of operation of this disclosure will be apparent to those skilled in the art without departing from the scope and spirit of the embodiments of the present disclosure.
Although the present disclosure has been described in connection with particular embodiments, it should be understood that the present disclosure as claimed should not be unduly limited to such particular embodiments. It is intended that the following claims define the scope of the present disclosure and that structures and methods within the scope of these claims and their equivalents be covered thereby.
In another aspect, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to request a reference data, and determine a sensitivity value associated with the analyte sensor based on the reference data.
Reference data may include an in vitro blood glucose measurement data.
Further, the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to calibrate the analyte sensor based at least in part on the determined sensitivity value.
Moreover, in still another aspect, there is provided one or more storage devices having processor readable code embodied thereon, said processor readable code for programming one or more processors to estimate an analyte level may comprise, positioning an analyte sensor in fluid contact with an analyte, detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
Various other modifications and alterations in the structure and method of operation of this disclosure will be apparent to those skilled in the art without departing from the scope and spirit of the embodiments of the present disclosure.
Although the present disclosure has been described in connection with particular embodiments, it should be understood that the present disclosure as claimed should not be unduly limited to such particular embodiments. It is intended that the following claims define the scope of the present disclosure and that structures and methods within the scope of these claims and their equivalents be covered thereby.
Claims (42)
1. A method, comprising:
positioning an analyte sensor in fluid contact with an analyte;
detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period;
categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal; and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
positioning an analyte sensor in fluid contact with an analyte;
detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period;
categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal; and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
2. The method of claim 1 wherein the signal from the analyte sensor is associated with a monitored analyte level.
3. The method of claim 1 wherein the detected attenuation in the signal from the analyte sensor is associated with an early signal attenuation condition.
4. The method of claim 1 wherein the predetermined time period does not exceed approximately 24 hours.
5. The method of claim 1 wherein categorizing the detected analyte sensor signal attenuation is based at least in part on a predetermined plurality of signal attenuation conditions.
6. The method of claim 5 wherein the plurality of signal attenuation conditions includes a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
7. The method of claim 6 including outputting data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
8. The method of claim 7 wherein outputting data associated with the monitored analyte level includes outputting data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
9. The method of claim 8 wherein the preset time period does not exceed approximately two hours.
10. The method of claim 8 including requesting a reference blood glucose measurement during the preset time period.
11. The method of claim 10 including calibrating the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
12. The method of claim 8 including disabling outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
13. The method of claim 1 wherein performing signal processing includes:
requesting a reference data; and determining a sensitivity value associated with the analyte sensor based on the reference data.
requesting a reference data; and determining a sensitivity value associated with the analyte sensor based on the reference data.
14. The method of claim 13 wherein the reference data includes an in vitro blood glucose measurement data.
15. The method of claim 13 including calibrating the analyte sensor based at least in part on the determined sensitivity value.
16. A method, comprising:
monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period; and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
monitoring for a signal level below a predetermined threshold associated with analyte level from an analyte sensor during a predefined time period; and reporting analyte level associated with the analyte sensor when the signal level monitored is not detected during the predefined time period.
17. The method of claim 16, wherein the predefined time period is less than approximately one hour.
18. The method of claim 16, including:
receiving a blood glucose measurement; and calibrating the analyte sensor based on the received blood glucose measurement.
receiving a blood glucose measurement; and calibrating the analyte sensor based on the received blood glucose measurement.
19. The method of claim 16 wherein the predetermined threshold is associated with one or more of an impending hypoglycemic state, or a predefined signal attenuation level.
20. The method of claim 16 wherein reporting the analyte level includes one or more of storing the analyte level, confirming the analyte level, or outputting the analyte level.
21. A method of initializing a glucose sensor, the method comprising:
inserting at least a portion of a glucose sensor beneath a skin surface of an individual;
analyzing glucose-related signal from the sensor to determine sensor stability;
and reporting glucose related information to the individual only when it is determined that the sensor is stable;
wherein the glucose related information is not reported prior to determination that the sensor is stable.
inserting at least a portion of a glucose sensor beneath a skin surface of an individual;
analyzing glucose-related signal from the sensor to determine sensor stability;
and reporting glucose related information to the individual only when it is determined that the sensor is stable;
wherein the glucose related information is not reported prior to determination that the sensor is stable.
22. The method of claim 21 wherein sensor stability is determined using reference data.
23. The method of claim 21 wherein the reference data comprises sampling blood of the individual.
24. The method of claim 21 wherein the reference data is obtained from a glucose test strip.
25. The method of claim 24 including analyzing the sensor signal to determine whether there exists a decrease in sensor signal.
26. The method of claim 24 wherein the analyte sensor reports the glucose related information in about one hour following the insertion.
27. An apparatus, comprising:
a data communication interface;
one or more processors operatively coupled to the data communication interface; and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to position an analyte sensor in fluid contact with an analyte, detect an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorize the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and perform signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
a data communication interface;
one or more processors operatively coupled to the data communication interface; and a memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to position an analyte sensor in fluid contact with an analyte, detect an attenuation in a signal from an analyte sensor after positioning during a predetermined time period, categorize the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal, and perform signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
28. The apparatus of claim 27 wherein the signal from the analyte sensor is associated with a monitored analyte level.
29. The apparatus of claim 27 wherein the detected attenuation in the signal from the analyte sensor is associated with an early signal attenuation condition.
30. The apparatus of claim 27 wherein the predetermined time period does not exceed approximately 24 hours.
31. The apparatus of claim wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to categorize the detected analyte sensor signal attenuation based at least in part on a predetermined plurality of signal attenuation conditions.
32. The apparatus of claim 31 wherein the plurality of signal attenuation conditions includes a reportable signal condition, a conditional reportable signal condition, and an unreportable signal condition.
33. The apparatus of claim 32 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to output data associated with the monitored analyte level based on the detected analyte sensor signal when the detected analyte sensor signal attenuation includes a reportable signal condition or a conditional reportable signal condition.
34. The apparatus of claim 33 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to output data for a preset time period when the detected analyte sensor signal attenuation includes the conditional reportable signal condition.
35. The apparatus of claim 34 wherein the preset time period does not exceed approximately two hours.
36. The apparatus of claim 34 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to request a reference blood glucose measurement during the preset time period.
37. The apparatus of claim 36 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to calibrate the analyte sensor signal based at least in part on the reference blood glucose measurement received during the preset time period.
38. The apparatus of claim 34 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to disable the outputting of the data associated with the monitored analyte level after the preset time period has elapsed.
39. The apparatus of claim 27 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to request a reference data, and determine a sensitivity value associated with the analyte sensor based on the reference data.
40. The apparatus of claim 39 wherein the reference data includes an in vitro blood glucose measurement data.
41. The apparatus of claim 39 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to calibrate the analyte sensor based at least in part on the determined sensitivity value.
42. One or more storage devices having processor readable code embodied thereon, said processor readable code for programming one or more processors to estimate an analyte level, comprising:
positioning an analyte sensor in fluid contact with an analyte;
detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period;
categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal; and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
positioning an analyte sensor in fluid contact with an analyte;
detecting an attenuation in a signal from an analyte sensor after positioning during a predetermined time period;
categorizing the detected attenuation in the analyte sensor signal based, at least in part, on one or more characteristics of the signal; and performing signal processing to generate a reportable data associated with the detected analyte sensor signal during the predetermined time period.
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Families Citing this family (140)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8480580B2 (en) | 1998-04-30 | 2013-07-09 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US8688188B2 (en) | 1998-04-30 | 2014-04-01 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US8346337B2 (en) | 1998-04-30 | 2013-01-01 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US8465425B2 (en) | 1998-04-30 | 2013-06-18 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US8974386B2 (en) | 1998-04-30 | 2015-03-10 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US8260393B2 (en) | 2003-07-25 | 2012-09-04 | Dexcom, Inc. | Systems and methods for replacing signal data artifacts in a glucose sensor data stream |
US8010174B2 (en) | 2003-08-22 | 2011-08-30 | Dexcom, Inc. | Systems and methods for replacing signal artifacts in a glucose sensor data stream |
US8282549B2 (en) | 2003-12-09 | 2012-10-09 | Dexcom, Inc. | Signal processing for continuous analyte sensor |
US8060173B2 (en) | 2003-08-01 | 2011-11-15 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US8676287B2 (en) | 2003-08-01 | 2014-03-18 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US7925321B2 (en) | 2003-08-01 | 2011-04-12 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US7774145B2 (en) | 2003-08-01 | 2010-08-10 | Dexcom, Inc. | Transcutaneous analyte sensor |
US20190357827A1 (en) | 2003-08-01 | 2019-11-28 | Dexcom, Inc. | Analyte sensor |
US8886273B2 (en) | 2003-08-01 | 2014-11-11 | Dexcom, Inc. | Analyte sensor |
US8160669B2 (en) | 2003-08-01 | 2012-04-17 | Dexcom, Inc. | Transcutaneous analyte sensor |
US8369919B2 (en) | 2003-08-01 | 2013-02-05 | Dexcom, Inc. | Systems and methods for processing sensor data |
US8761856B2 (en) | 2003-08-01 | 2014-06-24 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US7920906B2 (en) | 2005-03-10 | 2011-04-05 | Dexcom, Inc. | System and methods for processing analyte sensor data for sensor calibration |
US20140121989A1 (en) | 2003-08-22 | 2014-05-01 | Dexcom, Inc. | Systems and methods for processing analyte sensor data |
WO2005051170A2 (en) | 2003-11-19 | 2005-06-09 | Dexcom, Inc. | Integrated receiver for continuous analyte sensor |
US9247900B2 (en) | 2004-07-13 | 2016-02-02 | Dexcom, Inc. | Analyte sensor |
US8423114B2 (en) | 2006-10-04 | 2013-04-16 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
DE602004029092D1 (en) | 2003-12-05 | 2010-10-21 | Dexcom Inc | CALIBRATION METHODS FOR A CONTINUOUSLY WORKING ANALYTIC SENSOR |
US11633133B2 (en) | 2003-12-05 | 2023-04-25 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US7946984B2 (en) | 2004-07-13 | 2011-05-24 | Dexcom, Inc. | Transcutaneous analyte sensor |
US9636450B2 (en) | 2007-02-19 | 2017-05-02 | Udo Hoss | Pump system modular components for delivering medication and analyte sensing at seperate insertion sites |
US7697967B2 (en) | 2005-12-28 | 2010-04-13 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte sensor insertion |
US20100331646A1 (en) * | 2009-06-30 | 2010-12-30 | Abbott Diabetes Care Inc. | Health Management Devices and Methods |
US20080314395A1 (en) | 2005-08-31 | 2008-12-25 | Theuniversity Of Virginia Patent Foundation | Accuracy of Continuous Glucose Sensors |
US11298058B2 (en) | 2005-12-28 | 2022-04-12 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte sensor insertion |
US7885698B2 (en) | 2006-02-28 | 2011-02-08 | Abbott Diabetes Care Inc. | Method and system for providing continuous calibration of implantable analyte sensors |
US7826879B2 (en) | 2006-02-28 | 2010-11-02 | Abbott Diabetes Care Inc. | Analyte sensors and methods of use |
US8224415B2 (en) | 2009-01-29 | 2012-07-17 | Abbott Diabetes Care Inc. | Method and device for providing offset model based calibration for analyte sensor |
US9392969B2 (en) | 2008-08-31 | 2016-07-19 | Abbott Diabetes Care Inc. | Closed loop control and signal attenuation detection |
US9675290B2 (en) | 2012-10-30 | 2017-06-13 | Abbott Diabetes Care Inc. | Sensitivity calibration of in vivo sensors used to measure analyte concentration |
US7630748B2 (en) | 2006-10-25 | 2009-12-08 | Abbott Diabetes Care Inc. | Method and system for providing analyte monitoring |
US8219173B2 (en) | 2008-09-30 | 2012-07-10 | Abbott Diabetes Care Inc. | Optimizing analyte sensor calibration |
US8346335B2 (en) | 2008-03-28 | 2013-01-01 | Abbott Diabetes Care Inc. | Analyte sensor calibration management |
EP2106238A4 (en) | 2006-10-26 | 2011-03-09 | Abbott Diabetes Care Inc | Method, system and computer program product for real-time detection of sensitivity decline in analyte sensors |
US8930203B2 (en) | 2007-02-18 | 2015-01-06 | Abbott Diabetes Care Inc. | Multi-function analyte test device and methods therefor |
ES2817503T3 (en) | 2007-04-14 | 2021-04-07 | Abbott Diabetes Care Inc | Procedure and apparatus for providing data processing and control in a medical communication system |
CA2683959C (en) | 2007-04-14 | 2017-08-29 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
EP2146625B1 (en) | 2007-04-14 | 2019-08-14 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
CA2683953C (en) | 2007-04-14 | 2016-08-02 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
DK1983456T3 (en) * | 2007-04-19 | 2013-11-25 | Hoffmann La Roche | Method of setting a basal rate profile for an insulin pump |
US8239166B2 (en) | 2007-05-14 | 2012-08-07 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8103471B2 (en) | 2007-05-14 | 2012-01-24 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8560038B2 (en) | 2007-05-14 | 2013-10-15 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8444560B2 (en) | 2007-05-14 | 2013-05-21 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US9125548B2 (en) | 2007-05-14 | 2015-09-08 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US10002233B2 (en) | 2007-05-14 | 2018-06-19 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8600681B2 (en) | 2007-05-14 | 2013-12-03 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8260558B2 (en) | 2007-05-14 | 2012-09-04 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8834366B2 (en) | 2007-07-31 | 2014-09-16 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte sensor calibration |
US8216138B1 (en) | 2007-10-23 | 2012-07-10 | Abbott Diabetes Care Inc. | Correlation of alternative site blood and interstitial fluid glucose concentrations to venous glucose concentration |
US8417312B2 (en) | 2007-10-25 | 2013-04-09 | Dexcom, Inc. | Systems and methods for processing sensor data |
US20090164239A1 (en) | 2007-12-19 | 2009-06-25 | Abbott Diabetes Care, Inc. | Dynamic Display Of Glucose Information |
US11730407B2 (en) | 2008-03-28 | 2023-08-22 | Dexcom, Inc. | Polymer membranes for continuous analyte sensors |
CN102047101A (en) * | 2008-03-28 | 2011-05-04 | 德克斯康公司 | Polymer membranes for continuous analyte sensors |
US8583204B2 (en) | 2008-03-28 | 2013-11-12 | Dexcom, Inc. | Polymer membranes for continuous analyte sensors |
US8682408B2 (en) * | 2008-03-28 | 2014-03-25 | Dexcom, Inc. | Polymer membranes for continuous analyte sensors |
US7826382B2 (en) | 2008-05-30 | 2010-11-02 | Abbott Diabetes Care Inc. | Close proximity communication device and methods |
US8924159B2 (en) | 2008-05-30 | 2014-12-30 | Abbott Diabetes Care Inc. | Method and apparatus for providing glycemic control |
US8591410B2 (en) | 2008-05-30 | 2013-11-26 | Abbott Diabetes Care Inc. | Method and apparatus for providing glycemic control |
WO2010009172A1 (en) | 2008-07-14 | 2010-01-21 | Abbott Diabetes Care Inc. | Closed loop control system interface and methods |
US20100057040A1 (en) | 2008-08-31 | 2010-03-04 | Abbott Diabetes Care, Inc. | Robust Closed Loop Control And Methods |
US9943644B2 (en) | 2008-08-31 | 2018-04-17 | Abbott Diabetes Care Inc. | Closed loop control with reference measurement and methods thereof |
US8622988B2 (en) | 2008-08-31 | 2014-01-07 | Abbott Diabetes Care Inc. | Variable rate closed loop control and methods |
US8734422B2 (en) | 2008-08-31 | 2014-05-27 | Abbott Diabetes Care Inc. | Closed loop control with improved alarm functions |
US8986208B2 (en) | 2008-09-30 | 2015-03-24 | Abbott Diabetes Care Inc. | Analyte sensor sensitivity attenuation mitigation |
US9326707B2 (en) | 2008-11-10 | 2016-05-03 | Abbott Diabetes Care Inc. | Alarm characterization for analyte monitoring devices and systems |
US8103456B2 (en) * | 2009-01-29 | 2012-01-24 | Abbott Diabetes Care Inc. | Method and device for early signal attenuation detection using blood glucose measurements |
US8497777B2 (en) | 2009-04-15 | 2013-07-30 | Abbott Diabetes Care Inc. | Analyte monitoring system having an alert |
WO2010121229A1 (en) | 2009-04-16 | 2010-10-21 | Abbott Diabetes Care Inc. | Analyte sensor calibration management |
US8483967B2 (en) * | 2009-04-29 | 2013-07-09 | Abbott Diabetes Care Inc. | Method and system for providing real time analyte sensor calibration with retrospective backfill |
EP2424426B1 (en) | 2009-04-29 | 2020-01-08 | Abbott Diabetes Care, Inc. | Method and system for providing data communication in continuous glucose monitoring and management system |
EP3936032A1 (en) | 2009-07-23 | 2022-01-12 | Abbott Diabetes Care, Inc. | Real time management of data relating to physiological control of glucose levels |
DK3689237T3 (en) | 2009-07-23 | 2021-08-16 | Abbott Diabetes Care Inc | Method of preparation and system for continuous analyte measurement |
WO2011014851A1 (en) | 2009-07-31 | 2011-02-03 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte monitoring system calibration accuracy |
US8898069B2 (en) * | 2009-08-28 | 2014-11-25 | The Invention Science Fund I, Llc | Devices and methods for detecting an analyte in salivary fluid |
US9024766B2 (en) | 2009-08-28 | 2015-05-05 | The Invention Science Fund, Llc | Beverage containers with detection capability |
ES2912584T3 (en) | 2009-08-31 | 2022-05-26 | Abbott Diabetes Care Inc | A glucose monitoring system and method |
US9314195B2 (en) | 2009-08-31 | 2016-04-19 | Abbott Diabetes Care Inc. | Analyte signal processing device and methods |
WO2011041469A1 (en) | 2009-09-29 | 2011-04-07 | Abbott Diabetes Care Inc. | Method and apparatus for providing notification function in analyte monitoring systems |
WO2011053881A1 (en) | 2009-10-30 | 2011-05-05 | Abbott Diabetes Care Inc. | Method and apparatus for detecting false hypoglycemic conditions |
WO2011112753A1 (en) | 2010-03-10 | 2011-09-15 | Abbott Diabetes Care Inc. | Systems, devices and methods for managing glucose levels |
ES2881798T3 (en) | 2010-03-24 | 2021-11-30 | Abbott Diabetes Care Inc | Medical device inserters and medical device insertion and use procedures |
CN102469941B (en) | 2010-04-16 | 2016-04-13 | 艾伯特糖尿病护理公司 | Analyze thing surveillance equipment and method |
US8726266B2 (en) | 2010-05-24 | 2014-05-13 | Abbott Diabetes Care Inc. | Method and system for updating a medical device |
US8635046B2 (en) | 2010-06-23 | 2014-01-21 | Abbott Diabetes Care Inc. | Method and system for evaluating analyte sensor response characteristics |
US10092229B2 (en) | 2010-06-29 | 2018-10-09 | Abbott Diabetes Care Inc. | Calibration of analyte measurement system |
US11213226B2 (en) | 2010-10-07 | 2022-01-04 | Abbott Diabetes Care Inc. | Analyte monitoring devices and methods |
WO2012108936A1 (en) | 2011-02-11 | 2012-08-16 | Abbott Diabetes Care Inc. | Data synchronization between two or more analyte detecting devices in a database |
WO2012108939A1 (en) | 2011-02-11 | 2012-08-16 | Abbott Diabetes Care Inc. | Feedback from cloud or hcp to payer or patient via meter or cell phone |
WO2012108938A1 (en) | 2011-02-11 | 2012-08-16 | Abbott Diabetes Care Inc. | Software applications residing on handheld analyte determining devices |
US10136845B2 (en) | 2011-02-28 | 2018-11-27 | Abbott Diabetes Care Inc. | Devices, systems, and methods associated with analyte monitoring devices and devices incorporating the same |
US8844007B2 (en) * | 2011-04-08 | 2014-09-23 | Dexcom, Inc. | Systems and methods for processing and transmitting sensor data |
DK3575796T3 (en) | 2011-04-15 | 2021-01-18 | Dexcom Inc | ADVANCED ANALYZE SENSOR CALIBRATION AND ERROR DETECTION |
CN103907115B (en) * | 2011-05-11 | 2017-10-20 | 艾森斯收购股份有限责任公司 | The backward calibration of sensing data |
WO2013066849A1 (en) | 2011-10-31 | 2013-05-10 | Abbott Diabetes Care Inc. | Model based variable risk false glucose threshold alarm prevention mechanism |
US8710993B2 (en) | 2011-11-23 | 2014-04-29 | Abbott Diabetes Care Inc. | Mitigating single point failure of devices in an analyte monitoring system and methods thereof |
US9317656B2 (en) | 2011-11-23 | 2016-04-19 | Abbott Diabetes Care Inc. | Compatibility mechanisms for devices in a continuous analyte monitoring system and methods thereof |
WO2013078426A2 (en) | 2011-11-25 | 2013-05-30 | Abbott Diabetes Care Inc. | Analyte monitoring system and methods of use |
EP2825096B1 (en) * | 2012-03-16 | 2023-04-26 | Dexcom, Inc. | Systems and methods for processing analyte sensor data |
CN108362867B (en) | 2012-07-26 | 2020-04-14 | 安晟信医疗科技控股公司 | Biosensor meter for determining an analyte concentration in a fluid and method of operating the same |
EP3395252A1 (en) | 2012-08-30 | 2018-10-31 | Abbott Diabetes Care, Inc. | Dropout detection in continuous analyte monitoring data during data excursions |
US9907492B2 (en) | 2012-09-26 | 2018-03-06 | Abbott Diabetes Care Inc. | Method and apparatus for improving lag correction during in vivo measurement of analyte concentration with analyte concentration variability and range data |
US9788765B2 (en) * | 2012-09-28 | 2017-10-17 | Dexcom, Inc. | Zwitterion surface modifications for continuous sensors |
US9329159B2 (en) | 2013-03-08 | 2016-05-03 | Ecolab Usa Inc. | Methods and systems for analyzing a liquid medium |
US10335075B2 (en) | 2013-03-14 | 2019-07-02 | Dexcom, Inc. | Advanced calibration for analyte sensors |
US10433773B1 (en) | 2013-03-15 | 2019-10-08 | Abbott Diabetes Care Inc. | Noise rejection methods and apparatus for sparsely sampled analyte sensor data |
US9474475B1 (en) | 2013-03-15 | 2016-10-25 | Abbott Diabetes Care Inc. | Multi-rate analyte sensor data collection with sample rate configurable signal processing |
WO2014152034A1 (en) | 2013-03-15 | 2014-09-25 | Abbott Diabetes Care Inc. | Sensor fault detection using analyte sensor data pattern comparison |
CN109222991B (en) | 2013-04-30 | 2022-04-19 | 雅培糖尿病护理公司 | Method for supplying power in living body analyte monitoring environment and monitoring system |
US9233204B2 (en) | 2014-01-31 | 2016-01-12 | Aseko, Inc. | Insulin management |
US9486580B2 (en) | 2014-01-31 | 2016-11-08 | Aseko, Inc. | Insulin management |
EP4151150A1 (en) | 2014-03-30 | 2023-03-22 | Abbott Diabetes Care, Inc. | Method and apparatus for determining meal start and peak events in analyte monitoring systems |
DE202015010002U1 (en) * | 2014-05-21 | 2022-12-12 | Abbott Diabetes Care, Inc. | Management of multiple devices within an analyte monitoring environment |
JP6503924B2 (en) * | 2014-06-26 | 2019-04-24 | 東洋インキScホールディングス株式会社 | Electrode sheet and sensor using the same |
US10598624B2 (en) | 2014-10-23 | 2020-03-24 | Abbott Diabetes Care Inc. | Electrodes having at least one sensing structure and methods for making and using the same |
US11081226B2 (en) | 2014-10-27 | 2021-08-03 | Aseko, Inc. | Method and controller for administering recommended insulin dosages to a patient |
JP6989262B2 (en) | 2014-10-27 | 2022-01-05 | アセコー インコーポレイテッド | Subcutaneous outpatient management |
CA2987399A1 (en) * | 2015-05-27 | 2016-12-01 | Senseonics, Incorporated | Wireless analyte monitoring |
WO2017011346A1 (en) | 2015-07-10 | 2017-01-19 | Abbott Diabetes Care Inc. | System, device and method of dynamic glucose profile response to physiological parameters |
US10888272B2 (en) | 2015-07-10 | 2021-01-12 | Abbott Diabetes Care Inc. | Systems, devices, and methods for meal information collection, meal assessment, and analyte data correlation |
JP6858751B2 (en) | 2015-08-20 | 2021-04-14 | アセコー インコーポレイテッド | Diabetes Management Therapy Advisor |
JP6864819B2 (en) * | 2016-06-30 | 2021-04-28 | 富士フイルムビジネスイノベーション株式会社 | Information processing equipment and programs |
EP3558117A1 (en) | 2016-12-20 | 2019-10-30 | Abbott Diabetes Care Inc. | Systems, devices and methods for wireless communications in analyte monitoring devices |
RU2766749C2 (en) * | 2016-12-22 | 2022-03-15 | Санвита Мэдикал, Ллс | Continuous glucose monitoring system and method |
CN108281200A (en) * | 2016-12-30 | 2018-07-13 | 上海移宇科技股份有限公司 | A kind of method of the adjustment algorithm in dynamic blood sugar monitoring system and the dynamic blood sugar monitoring system of application this method |
US11596330B2 (en) | 2017-03-21 | 2023-03-07 | Abbott Diabetes Care Inc. | Methods, devices and system for providing diabetic condition diagnosis and therapy |
US11331022B2 (en) | 2017-10-24 | 2022-05-17 | Dexcom, Inc. | Pre-connected analyte sensors |
US20190120785A1 (en) | 2017-10-24 | 2019-04-25 | Dexcom, Inc. | Pre-connected analyte sensors |
US20220031250A1 (en) * | 2018-09-14 | 2022-02-03 | The Regents Of The University Of California | Toothbrush-derived digital phenotypes for understanding and modulating behaviors and health |
WO2020227573A1 (en) * | 2019-05-09 | 2020-11-12 | Waveform Technologies, Inc. | Systems and methods for biosensor cross-calibration |
CN111076372B (en) * | 2019-12-25 | 2021-02-19 | 大连理工大学 | Online identification and repair method for sensor error in primary return air conditioning system |
DK4048152T3 (en) | 2020-07-29 | 2024-03-11 | Biolinq Incorporated | SYSTEM FOR CONTINUOUS ANALYTE MONITORING WITH MICRON NEEDLE ARRANGEMENT |
USD957438S1 (en) | 2020-07-29 | 2022-07-12 | Abbott Diabetes Care Inc. | Display screen or portion thereof with graphical user interface |
EP4153276A4 (en) | 2021-05-08 | 2023-11-08 | Biolinq, Inc. | Fault detection for microneedle array based continuous analyte monitoring device |
WO2023044889A1 (en) * | 2021-09-27 | 2023-03-30 | Medtrum Technologies Inc. | Analyte detection system |
Family Cites Families (745)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB1191363A (en) | 1968-02-19 | 1970-05-13 | Pavelle Ltd | Improvements in or relating to Electronic Thermostats. |
US3949388A (en) | 1972-11-13 | 1976-04-06 | Monitron Industries, Inc. | Physiological sensor and transmitter |
US3926760A (en) | 1973-09-28 | 1975-12-16 | Du Pont | Process for electrophoretic deposition of polymer |
US4245634A (en) | 1975-01-22 | 1981-01-20 | Hospital For Sick Children | Artificial beta cell |
US4036749A (en) | 1975-04-30 | 1977-07-19 | Anderson Donald R | Purification of saline water |
US3960497A (en) | 1975-08-19 | 1976-06-01 | Beckman Instruments, Inc. | Chemical analyzer with automatic calibration |
US4033330A (en) | 1975-09-08 | 1977-07-05 | Hewlett-Packard Company | Transcutaneous pH measuring instrument |
US4055175A (en) | 1976-05-07 | 1977-10-25 | Miles Laboratories, Inc. | Blood glucose control apparatus |
US4129128A (en) | 1977-02-23 | 1978-12-12 | Mcfarlane Richard H | Securing device for catheter placement assembly |
US4344438A (en) | 1978-08-02 | 1982-08-17 | The United States Of America As Represented By The Department Of Health, Education And Welfare | Optical sensor of plasma constituents |
AU530979B2 (en) | 1978-12-07 | 1983-08-04 | Aus. Training Aids Pty. Ltd., | Detecting position of bullet fired at target |
US4373527B1 (en) | 1979-04-27 | 1995-06-27 | Univ Johns Hopkins | Implantable programmable medication infusion system |
CS210174B1 (en) | 1979-07-12 | 1982-01-29 | Ivan Emmer | Method of making the electric hygrometric sensor |
US4425920A (en) | 1980-10-24 | 1984-01-17 | Purdue Research Foundation | Apparatus and method for measurement and control of blood pressure |
US4327725A (en) | 1980-11-25 | 1982-05-04 | Alza Corporation | Osmotic device with hydrogel driving member |
US4392849A (en) | 1981-07-27 | 1983-07-12 | The Cleveland Clinic Foundation | Infusion pump controller |
DE3138194A1 (en) | 1981-09-25 | 1983-04-14 | Basf Ag, 6700 Ludwigshafen | WATER-INSOLUBLE POROESES PROTEIN MATERIAL, THEIR PRODUCTION AND USE |
US4494950A (en) | 1982-01-19 | 1985-01-22 | The Johns Hopkins University | Plural module medication delivery system |
US4462048A (en) | 1982-02-11 | 1984-07-24 | Rca Corporation | Noise reduction circuitry for audio signals |
FI831399L (en) | 1982-04-29 | 1983-10-30 | Agripat Sa | KONTAKTLINS AV HAERDAD POLYVINYL ALCOHOL |
EP0098592A3 (en) | 1982-07-06 | 1985-08-21 | Fujisawa Pharmaceutical Co., Ltd. | Portable artificial pancreas |
US4509531A (en) | 1982-07-28 | 1985-04-09 | Teledyne Industries, Inc. | Personal physiological monitor |
US4464170A (en) | 1982-09-29 | 1984-08-07 | Miles Laboratories, Inc. | Blood glucose control apparatus and method |
US4527240A (en) | 1982-12-29 | 1985-07-02 | Kvitash Vadim I | Balascopy method for detecting and rapidly evaluating multiple imbalances within multi-parametric systems |
US5509410A (en) | 1983-06-06 | 1996-04-23 | Medisense, Inc. | Strip electrode including screen printing of a single layer |
CA1226036A (en) | 1983-05-05 | 1987-08-25 | Irving J. Higgins | Analytical equipment and sensor electrodes therefor |
US4538616A (en) | 1983-07-25 | 1985-09-03 | Robert Rogoff | Blood sugar level sensing and monitoring transducer |
DE3429596A1 (en) | 1984-08-10 | 1986-02-20 | Siemens AG, 1000 Berlin und 8000 München | DEVICE FOR THE PHYSIOLOGICAL FREQUENCY CONTROL OF A PACEMAKER PROVIDED WITH A PICTURE ELECTRODE |
CA1254091A (en) | 1984-09-28 | 1989-05-16 | Vladimir Feingold | Implantable medication infusion system |
US4847785A (en) | 1985-01-22 | 1989-07-11 | International Business Machines Corp. | Interactive display for trend or bar graph |
US5279294A (en) | 1985-04-08 | 1994-01-18 | Cascade Medical, Inc. | Medical diagnostic system |
US4671288A (en) | 1985-06-13 | 1987-06-09 | The Regents Of The University Of California | Electrochemical cell sensor for continuous short-term use in tissues and blood |
US4890620A (en) | 1985-09-20 | 1990-01-02 | The Regents Of The University Of California | Two-dimensional diffusion glucose substrate sensing electrode |
US4757022A (en) | 1986-04-15 | 1988-07-12 | Markwell Medical Institute, Inc. | Biological fluid measuring device |
US4703756A (en) | 1986-05-06 | 1987-11-03 | The Regents Of The University Of California | Complete glucose monitoring system with an implantable, telemetered sensor module |
US4731726A (en) | 1986-05-19 | 1988-03-15 | Healthware Corporation | Patient-operated glucose monitor and diabetes management system |
US5055171A (en) | 1986-10-06 | 1991-10-08 | T And G Corporation | Ionic semiconductor materials and applications thereof |
US4777953A (en) | 1987-02-25 | 1988-10-18 | Ash Medical Systems, Inc. | Capillary filtration and collection method for long-term monitoring of blood constituents |
US4854322A (en) | 1987-02-25 | 1989-08-08 | Ash Medical Systems, Inc. | Capillary filtration and collection device for long-term monitoring of blood constituents |
US5002054A (en) | 1987-02-25 | 1991-03-26 | Ash Medical Systems, Inc. | Interstitial filtration and collection device and method for long-term monitoring of physiological constituents of the body |
US4759828A (en) | 1987-04-09 | 1988-07-26 | Nova Biomedical Corporation | Glucose electrode and method of determining glucose |
US4749985A (en) | 1987-04-13 | 1988-06-07 | United States Of America As Represented By The United States Department Of Energy | Functional relationship-based alarm processing |
EP0290683A3 (en) | 1987-05-01 | 1988-12-14 | Diva Medical Systems B.V. | Diabetes management system and apparatus |
GB8725936D0 (en) | 1987-11-05 | 1987-12-09 | Genetics Int Inc | Sensing system |
US4925268A (en) | 1988-07-25 | 1990-05-15 | Abbott Laboratories | Fiber-optic physiological probes |
EP0353328A1 (en) | 1988-08-03 | 1990-02-07 | Dräger Nederland B.V. | A polarographic-amperometric three-electrode sensor |
US5340722A (en) | 1988-08-24 | 1994-08-23 | Avl Medical Instruments Ag | Method for the determination of the concentration of an enzyme substrate and a sensor for carrying out the method |
US4995402A (en) | 1988-10-12 | 1991-02-26 | Thorne, Smith, Astill Technologies, Inc. | Medical droplet whole blood and like monitoring |
US5360404A (en) | 1988-12-14 | 1994-11-01 | Inviro Medical Devices Ltd. | Needle guard and needle assembly for syringe |
US5077476A (en) | 1990-06-27 | 1991-12-31 | Futrex, Inc. | Instrument for non-invasive measurement of blood glucose |
US5068536A (en) | 1989-01-19 | 1991-11-26 | Futrex, Inc. | Method for providing custom calibration for near infrared instruments for measurement of blood glucose |
DE69027233T2 (en) | 1989-03-03 | 1996-10-10 | Edward W Stark | Signal processing method and apparatus |
JPH02298855A (en) | 1989-03-20 | 1990-12-11 | Assoc Univ Inc | Electrochemical biosensor using immobilized enzyme and redox polymer |
US4953552A (en) | 1989-04-21 | 1990-09-04 | Demarzo Arthur P | Blood glucose monitoring system |
EP0396788A1 (en) | 1989-05-08 | 1990-11-14 | Dräger Nederland B.V. | Process and sensor for measuring the glucose content of glucosecontaining fluids |
FR2648353B1 (en) | 1989-06-16 | 1992-03-27 | Europhor Sa | MICRODIALYSIS PROBE |
US5431160A (en) | 1989-07-19 | 1995-07-11 | University Of New Mexico | Miniature implantable refillable glucose sensor and material therefor |
US4986271A (en) | 1989-07-19 | 1991-01-22 | The University Of New Mexico | Vivo refillable glucose sensor |
US5264104A (en) | 1989-08-02 | 1993-11-23 | Gregg Brian A | Enzyme electrodes |
US5262035A (en) | 1989-08-02 | 1993-11-16 | E. Heller And Company | Enzyme electrodes |
US5320725A (en) | 1989-08-02 | 1994-06-14 | E. Heller & Company | Electrode and method for the detection of hydrogen peroxide |
US5264105A (en) | 1989-08-02 | 1993-11-23 | Gregg Brian A | Enzyme electrodes |
US5568400A (en) | 1989-09-01 | 1996-10-22 | Stark; Edward W. | Multiplicative signal correction method and apparatus |
US5050612A (en) | 1989-09-12 | 1991-09-24 | Matsumura Kenneth N | Device for computer-assisted monitoring of the body |
US5082550A (en) | 1989-12-11 | 1992-01-21 | The United States Of America As Represented By The Department Of Energy | Enzyme electrochemical sensor electrode and method of making it |
US5342789A (en) | 1989-12-14 | 1994-08-30 | Sensor Technologies, Inc. | Method and device for detecting and quantifying glucose in body fluids |
US5051688A (en) | 1989-12-20 | 1991-09-24 | Rohm Co., Ltd. | Crossed coil meter driving device having a plurality of input parameters |
US5165407A (en) | 1990-04-19 | 1992-11-24 | The University Of Kansas | Implantable glucose sensor |
GB2243211A (en) | 1990-04-20 | 1991-10-23 | Philips Electronic Associated | Analytical instrument and method of calibrating an analytical instrument |
US5202261A (en) | 1990-07-19 | 1993-04-13 | Miles Inc. | Conductive sensors and their use in diagnostic assays |
WO1992005775A1 (en) | 1990-09-28 | 1992-04-16 | Pfizer Inc. | Dispensing device containing a hydrophobic medium |
US5251126A (en) | 1990-10-29 | 1993-10-05 | Miles Inc. | Diabetes data analysis and interpretation method |
ATE155575T1 (en) | 1990-12-12 | 1997-08-15 | Sherwood Medical Co | CALIBRATION OF AN INFRARED THERMOMETER USING AREA CALIBRATION CURVE REPRESENTATION |
US5354449A (en) | 1991-01-10 | 1994-10-11 | Band David M | pH electrode |
US5228449A (en) | 1991-01-22 | 1993-07-20 | Athanasios G. Christ | System and method for detecting out-of-hospital cardiac emergencies and summoning emergency assistance |
US5593852A (en) | 1993-12-02 | 1997-01-14 | Heller; Adam | Subcutaneous glucose electrode |
US5262305A (en) | 1991-03-04 | 1993-11-16 | E. Heller & Company | Interferant eliminating biosensors |
JPH04278450A (en) | 1991-03-04 | 1992-10-05 | Adam Heller | Biosensor and method for analyzing subject |
US5632272A (en) | 1991-03-07 | 1997-05-27 | Masimo Corporation | Signal processing apparatus |
US5469855A (en) | 1991-03-08 | 1995-11-28 | Exergen Corporation | Continuous temperature monitor |
US5135004A (en) | 1991-03-12 | 1992-08-04 | Incontrol, Inc. | Implantable myocardial ischemia monitor and related method |
US5204264A (en) | 1991-03-14 | 1993-04-20 | E. I. Du Pont De Nemours And Company | Method for validation of calibration standards in an automatic chemical analyzer |
US5122925A (en) | 1991-04-22 | 1992-06-16 | Control Products, Inc. | Package for electronic components |
US5328460A (en) | 1991-06-21 | 1994-07-12 | Pacesetter Infusion, Ltd. | Implantable medication infusion pump including self-contained acoustic fault detection apparatus |
US5231988A (en) | 1991-08-09 | 1993-08-03 | Cyberonics, Inc. | Treatment of endocrine disorders by nerve stimulation |
GB9120144D0 (en) | 1991-09-20 | 1991-11-06 | Imperial College | A dialysis electrode device |
US5322063A (en) | 1991-10-04 | 1994-06-21 | Eli Lilly And Company | Hydrophilic polyurethane membranes for electrochemical glucose sensors |
US5372427A (en) | 1991-12-19 | 1994-12-13 | Texas Instruments Incorporated | Temperature sensor |
US5285792A (en) | 1992-01-10 | 1994-02-15 | Physio-Control Corporation | System for producing prioritized alarm messages in a medical instrument |
US5246867A (en) | 1992-01-17 | 1993-09-21 | University Of Maryland At Baltimore | Determination and quantification of saccharides by luminescence lifetimes and energy transfer |
IL104365A0 (en) | 1992-01-31 | 1993-05-13 | Gensia Pharma | Method and apparatus for closed loop drug delivery |
US5328927A (en) | 1992-03-03 | 1994-07-12 | Merck Sharpe & Dohme, Ltd. | Hetercyclic compounds, processes for their preparation and pharmaceutical compositions containing them |
FR2690622B1 (en) | 1992-04-29 | 1995-01-20 | Chronotec | Programmable ambulatory infusion pump system. |
US5711001A (en) | 1992-05-08 | 1998-01-20 | Motorola, Inc. | Method and circuit for acquisition by a radio receiver |
GB9211402D0 (en) | 1992-05-29 | 1992-07-15 | Univ Manchester | Sensor devices |
DK95792A (en) | 1992-07-24 | 1994-01-25 | Radiometer As | Sensor for non-invasive, in vivo determination of an analyte and blood flow |
US6283761B1 (en) | 1992-09-08 | 2001-09-04 | Raymond Anthony Joao | Apparatus and method for processing and/or for providing healthcare information and/or healthcare-related information |
WO1994010553A1 (en) | 1992-10-23 | 1994-05-11 | Optex Biomedical, Inc. | Fibre-optic probe for the measurement of fluid parameters |
US5601435A (en) | 1994-11-04 | 1997-02-11 | Intercare | Method and apparatus for interactively monitoring a physiological condition and for interactively providing health related information |
US5899855A (en) | 1992-11-17 | 1999-05-04 | Health Hero Network, Inc. | Modular microprocessor-based health monitoring system |
US5956501A (en) | 1997-01-10 | 1999-09-21 | Health Hero Network, Inc. | Disease simulation system and method |
ZA938555B (en) | 1992-11-23 | 1994-08-02 | Lilly Co Eli | Technique to improve the performance of electrochemical sensors |
US5410326A (en) | 1992-12-04 | 1995-04-25 | Goldstein; Steven W. | Programmable remote control device for interacting with a plurality of remotely controlled devices |
US5299571A (en) | 1993-01-22 | 1994-04-05 | Eli Lilly And Company | Apparatus and method for implantation of sensors |
DK0622119T3 (en) | 1993-04-23 | 2000-04-10 | Roche Diagnostics Gmbh | Test element storage system |
US5384547A (en) | 1993-08-02 | 1995-01-24 | Motorola, Inc. | Apparatus and method for attenuating a multicarrier input signal of a linear device |
DE4329898A1 (en) | 1993-09-04 | 1995-04-06 | Marcus Dr Besson | Wireless medical diagnostic and monitoring device |
US5438983A (en) | 1993-09-13 | 1995-08-08 | Hewlett-Packard Company | Patient alarm detection using trend vector analysis |
US5582184A (en) | 1993-10-13 | 1996-12-10 | Integ Incorporated | Interstitial fluid collection and constituent measurement |
US5497772A (en) | 1993-11-19 | 1996-03-12 | Alfred E. Mann Foundation For Scientific Research | Glucose monitoring system |
US5791344A (en) | 1993-11-19 | 1998-08-11 | Alfred E. Mann Foundation For Scientific Research | Patient monitoring system |
DE4401400A1 (en) | 1994-01-19 | 1995-07-20 | Ernst Prof Dr Pfeiffer | Method and arrangement for continuously monitoring the concentration of a metabolite |
US5536249A (en) | 1994-03-09 | 1996-07-16 | Visionary Medical Products, Inc. | Pen-type injector with a microprocessor and blood characteristic monitor |
US5391250A (en) | 1994-03-15 | 1995-02-21 | Minimed Inc. | Method of fabricating thin film sensors |
US5390671A (en) | 1994-03-15 | 1995-02-21 | Minimed Inc. | Transcutaneous sensor insertion set |
AU2200895A (en) | 1994-04-04 | 1995-10-23 | Motorola, Inc. | Method and apparatus for activating and accessing remote meter interface devices |
US5609575A (en) | 1994-04-11 | 1997-03-11 | Graseby Medical Limited | Infusion pump and method with dose-rate calculation |
US5569186A (en) | 1994-04-25 | 1996-10-29 | Minimed Inc. | Closed loop infusion pump system with removable glucose sensor |
DE4415896A1 (en) | 1994-05-05 | 1995-11-09 | Boehringer Mannheim Gmbh | Analysis system for monitoring the concentration of an analyte in the blood of a patient |
US5472317A (en) | 1994-06-03 | 1995-12-05 | Minimed Inc. | Mounting clip for a medication infusion pump |
US5919141A (en) | 1994-11-15 | 1999-07-06 | Life Sensing Instrument Company, Inc. | Vital sign remote monitoring device |
US5586553A (en) | 1995-02-16 | 1996-12-24 | Minimed Inc. | Transcutaneous sensor insertion set |
US5568806A (en) | 1995-02-16 | 1996-10-29 | Minimed Inc. | Transcutaneous sensor insertion set |
US5564434A (en) | 1995-02-27 | 1996-10-15 | Medtronic, Inc. | Implantable capacitive absolute pressure and temperature sensor |
US5752512A (en) | 1995-05-10 | 1998-05-19 | Massachusetts Institute Of Technology | Apparatus and method for non-invasive blood analyte measurement |
US5628310A (en) | 1995-05-19 | 1997-05-13 | Joseph R. Lakowicz | Method and apparatus to perform trans-cutaneous analyte monitoring |
US5995860A (en) | 1995-07-06 | 1999-11-30 | Thomas Jefferson University | Implantable sensor and system for measurement and control of blood constituent levels |
US5555190A (en) | 1995-07-12 | 1996-09-10 | Micro Motion, Inc. | Method and apparatus for adaptive line enhancement in Coriolis mass flow meter measurement |
US7016713B2 (en) | 1995-08-09 | 2006-03-21 | Inlight Solutions, Inc. | Non-invasive determination of direction and rate of change of an analyte |
US5972199A (en) | 1995-10-11 | 1999-10-26 | E. Heller & Company | Electrochemical analyte sensors using thermostable peroxidase |
US5665222A (en) | 1995-10-11 | 1997-09-09 | E. Heller & Company | Soybean peroxidase electrochemical sensor |
US5748103A (en) | 1995-11-13 | 1998-05-05 | Vitalcom, Inc. | Two-way TDMA telemetry system with power conservation features |
US5711861A (en) | 1995-11-22 | 1998-01-27 | Ward; W. Kenneth | Device for monitoring changes in analyte concentration |
FI960636A (en) | 1996-02-12 | 1997-08-13 | Nokia Mobile Phones Ltd | A procedure for monitoring the health of a patient |
DE19618597B4 (en) | 1996-05-09 | 2005-07-21 | Institut für Diabetestechnologie Gemeinnützige Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm | Method for determining the concentration of tissue glucose |
US5735285A (en) | 1996-06-04 | 1998-04-07 | Data Critical Corp. | Method and hand-held apparatus for demodulating and viewing frequency modulated biomedical signals |
EP0914178B1 (en) | 1996-06-18 | 2003-03-12 | Alza Corporation | Device for enhancing transdermal agent delivery or sampling |
JP3581218B2 (en) | 1996-07-03 | 2004-10-27 | 株式会社東芝 | Mobile communication terminal device and its mobile phone and data terminal device |
CA2259254C (en) | 1996-07-08 | 2008-02-19 | Animas Corporation | Implantable sensor and system for in vivo measurement and control of fluid constituent levels |
US6544193B2 (en) | 1996-09-04 | 2003-04-08 | Marcio Marc Abreu | Noninvasive measurement of chemical substances |
US6027459A (en) | 1996-12-06 | 2000-02-22 | Abbott Laboratories | Method and apparatus for obtaining blood for diagnostic tests |
US5964993A (en) | 1996-12-19 | 1999-10-12 | Implanted Biosystems Inc. | Glucose sensor |
US5914026A (en) | 1997-01-06 | 1999-06-22 | Implanted Biosystems Inc. | Implantable sensor employing an auxiliary electrode |
US6032119A (en) | 1997-01-16 | 2000-02-29 | Health Hero Network, Inc. | Personalized display of health information |
US6122351A (en) | 1997-01-21 | 2000-09-19 | Med Graph, Inc. | Method and system aiding medical diagnosis and treatment |
US6607509B2 (en) | 1997-12-31 | 2003-08-19 | Medtronic Minimed, Inc. | Insertion device for an insertion set and method of using the same |
US6093172A (en) | 1997-02-05 | 2000-07-25 | Minimed Inc. | Injector for a subcutaneous insertion set |
DE69809391T2 (en) | 1997-02-06 | 2003-07-10 | Therasense Inc | SMALL VOLUME SENSOR FOR IN-VITRO DETERMINATION |
EP1011426A1 (en) | 1997-02-26 | 2000-06-28 | Diasense, Inc. | Individual calibration of blood glucose for supporting noninvasive self-monitoring blood glucose |
US6159147A (en) | 1997-02-28 | 2000-12-12 | Qrs Diagnostics, Llc | Personal computer card for collection of real-time biological data |
US7657297B2 (en) | 2004-05-03 | 2010-02-02 | Dexcom, Inc. | Implantable analyte sensor |
US20050033132A1 (en) | 1997-03-04 | 2005-02-10 | Shults Mark C. | Analyte measuring device |
US6001067A (en) | 1997-03-04 | 1999-12-14 | Shults; Mark C. | Device and method for determining analyte levels |
US6741877B1 (en) | 1997-03-04 | 2004-05-25 | Dexcom, Inc. | Device and method for determining analyte levels |
US9155496B2 (en) | 1997-03-04 | 2015-10-13 | Dexcom, Inc. | Low oxygen in vivo analyte sensor |
US7899511B2 (en) | 2004-07-13 | 2011-03-01 | Dexcom, Inc. | Low oxygen in vivo analyte sensor |
US6862465B2 (en) | 1997-03-04 | 2005-03-01 | Dexcom, Inc. | Device and method for determining analyte levels |
US7192450B2 (en) | 2003-05-21 | 2007-03-20 | Dexcom, Inc. | Porous membranes for use with implantable devices |
US6558321B1 (en) | 1997-03-04 | 2003-05-06 | Dexcom, Inc. | Systems and methods for remote monitoring and modulation of medical devices |
US6699187B2 (en) | 1997-03-27 | 2004-03-02 | Medtronic, Inc. | System and method for providing remote expert communications and video capabilities for use during a medical procedure |
US6270455B1 (en) | 1997-03-28 | 2001-08-07 | Health Hero Network, Inc. | Networked system for interactive communications and remote monitoring of drug delivery |
US5942979A (en) | 1997-04-07 | 1999-08-24 | Luppino; Richard | On guard vehicle safety warning system |
US5961451A (en) | 1997-04-07 | 1999-10-05 | Motorola, Inc. | Noninvasive apparatus having a retaining member to retain a removable biosensor |
US5935224A (en) | 1997-04-24 | 1999-08-10 | Microsoft Corporation | Method and apparatus for adaptively coupling an external peripheral device to either a universal serial bus port on a computer or hub or a game port on a computer |
US7267665B2 (en) | 1999-06-03 | 2007-09-11 | Medtronic Minimed, Inc. | Closed loop system for controlling insulin infusion |
US5954643A (en) | 1997-06-09 | 1999-09-21 | Minimid Inc. | Insertion set for a transcutaneous sensor |
US6558351B1 (en) | 1999-06-03 | 2003-05-06 | Medtronic Minimed, Inc. | Closed loop system for controlling insulin infusion |
EP0990151A2 (en) | 1997-06-16 | 2000-04-05 | ELAN CORPORATION, Plc | Methods of calibrating and testing a sensor for (in vivo) measurement of an analyte and devices for use in such methods |
US6066243A (en) | 1997-07-22 | 2000-05-23 | Diametrics Medical, Inc. | Portable immediate response medical analyzer having multiple testing modules |
US6259937B1 (en) | 1997-09-12 | 2001-07-10 | Alfred E. Mann Foundation | Implantable substrate sensor |
DE19836401A1 (en) | 1997-09-19 | 2000-02-17 | Salcomp Oy Salo | Device for charging accumulators |
US6117290A (en) | 1997-09-26 | 2000-09-12 | Pepex Biomedical, Llc | System and method for measuring a bioanalyte such as lactate |
US5904671A (en) | 1997-10-03 | 1999-05-18 | Navot; Nir | Tampon wetness detection system |
US6119028A (en) | 1997-10-20 | 2000-09-12 | Alfred E. Mann Foundation | Implantable enzyme-based monitoring systems having improved longevity due to improved exterior surfaces |
US6088608A (en) | 1997-10-20 | 2000-07-11 | Alfred E. Mann Foundation | Electrochemical sensor and integrity tests therefor |
FI107080B (en) | 1997-10-27 | 2001-05-31 | Nokia Mobile Phones Ltd | measuring device |
US6044285A (en) | 1997-11-12 | 2000-03-28 | Lightouch Medical, Inc. | Method for non-invasive measurement of an analyte |
WO1999027849A1 (en) | 1997-12-04 | 1999-06-10 | Roche Diagnostics Corporation | Instrument setup utility program |
CA2547299C (en) | 1997-12-04 | 2009-03-03 | Roche Diagnostics Corporation | Instrument and method |
US6579690B1 (en) | 1997-12-05 | 2003-06-17 | Therasense, Inc. | Blood analyte monitoring through subcutaneous measurement |
CA2484271C (en) | 1997-12-31 | 2007-04-24 | Medtronic Minimed, Inc. | Insertion device for an insertion set and method of using the same |
US6103033A (en) | 1998-03-04 | 2000-08-15 | Therasense, Inc. | Process for producing an electrochemical biosensor |
US6134461A (en) | 1998-03-04 | 2000-10-17 | E. Heller & Company | Electrochemical analyte |
US6024699A (en) | 1998-03-13 | 2000-02-15 | Healthware Corporation | Systems, methods and computer program products for monitoring, diagnosing and treating medical conditions of remotely located patients |
US6721582B2 (en) | 1999-04-06 | 2004-04-13 | Argose, Inc. | Non-invasive tissue glucose level monitoring |
JPH11296598A (en) | 1998-04-07 | 1999-10-29 | Seizaburo Arita | System and method for predicting blood-sugar level and record medium where same method is recorded |
US8346337B2 (en) | 1998-04-30 | 2013-01-01 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US6949816B2 (en) | 2003-04-21 | 2005-09-27 | Motorola, Inc. | Semiconductor component having first surface area for electrically coupling to a semiconductor chip and second surface area for electrically coupling to a substrate, and method of manufacturing same |
US8974386B2 (en) | 1998-04-30 | 2015-03-10 | Abbott Diabetes Care Inc. | Analyte monitoring device and methods of use |
US6175752B1 (en) | 1998-04-30 | 2001-01-16 | Therasense, Inc. | Analyte monitoring device and methods of use |
WO1999058050A1 (en) | 1998-05-13 | 1999-11-18 | Cygnus, Inc. | Signal processing for measurement of physiological analytes |
EP1077634B1 (en) | 1998-05-13 | 2003-07-30 | Cygnus, Inc. | Monitoring of physiological analytes |
US7043287B1 (en) | 1998-05-18 | 2006-05-09 | Abbott Laboratories | Method for modulating light penetration depth in tissue and diagnostic applications using same |
US6121611A (en) | 1998-05-20 | 2000-09-19 | Molecular Imaging Corporation | Force sensing probe for scanning probe microscopy |
US6223283B1 (en) | 1998-07-17 | 2001-04-24 | Compaq Computer Corporation | Method and apparatus for identifying display monitor functionality and compatibility |
US6493069B1 (en) | 1998-07-24 | 2002-12-10 | Terumo Kabushiki Kaisha | Method and instrument for measuring blood sugar level |
US6554798B1 (en) | 1998-08-18 | 2003-04-29 | Medtronic Minimed, Inc. | External infusion device with remote programming, bolus estimator and/or vibration alarm capabilities |
US6248067B1 (en) | 1999-02-05 | 2001-06-19 | Minimed Inc. | Analyte sensor and holter-type monitor system and method of using the same |
US6480753B1 (en) | 1998-09-04 | 2002-11-12 | Ncr Corporation | Communications, particularly in the domestic environment |
KR20000019716A (en) | 1998-09-15 | 2000-04-15 | 박호군 | Composition comprising bioflavonoid compounds for descending blood sugar |
US6740518B1 (en) | 1998-09-17 | 2004-05-25 | Clinical Micro Sensors, Inc. | Signal detection techniques for the detection of analytes |
US6254586B1 (en) | 1998-09-25 | 2001-07-03 | Minimed Inc. | Method and kit for supplying a fluid to a subcutaneous placement site |
US6402689B1 (en) | 1998-09-30 | 2002-06-11 | Sicel Technologies, Inc. | Methods, systems, and associated implantable devices for dynamic monitoring of physiological and biological properties of tumors |
DE69908602T2 (en) | 1998-09-30 | 2004-06-03 | Cygnus, Inc., Redwood City | METHOD AND DEVICE FOR PREDICTING PHYSIOLOGICAL MEASUREMENTS |
US6338790B1 (en) | 1998-10-08 | 2002-01-15 | Therasense, Inc. | Small volume in vitro analyte sensor with diffusible or non-leachable redox mediator |
WO2000019887A1 (en) | 1998-10-08 | 2000-04-13 | Minimed Inc. | Telemetered characteristic monitor system |
US6591125B1 (en) | 2000-06-27 | 2003-07-08 | Therasense, Inc. | Small volume in vitro analyte sensor with diffusible or non-leachable redox mediator |
EP1126779A4 (en) | 1998-11-03 | 2003-05-07 | Shell Allan Michael | Hand held physiological signal acquisition device |
US6602469B1 (en) | 1998-11-09 | 2003-08-05 | Lifestream Technologies, Inc. | Health monitoring and diagnostic device and network-based health assessment and medical records maintenance system |
US6497729B1 (en) | 1998-11-20 | 2002-12-24 | The University Of Connecticut | Implant coating for control of tissue/implant interactions |
US7436511B2 (en) | 1999-01-22 | 2008-10-14 | Sensys Medical, Inc. | Analyte filter method and apparatus |
EP1135052A1 (en) | 1999-02-12 | 2001-09-26 | Cygnus, Inc. | Devices and methods for frequent measurement of an analyte present in a biological system |
JP2002537031A (en) | 1999-02-18 | 2002-11-05 | バイオバルブ テクノロジーズ インコーポレイテッド | Electroactive pores |
US6424847B1 (en) * | 1999-02-25 | 2002-07-23 | Medtronic Minimed, Inc. | Glucose monitor calibration methods |
US6360888B1 (en) | 1999-02-25 | 2002-03-26 | Minimed Inc. | Glucose sensor package system |
US7577469B1 (en) | 1999-03-11 | 2009-08-18 | Jack L. Aronowitz | Noninvasive transdermal systems for detecting an analyte in a biological fluid and methods |
GB9907815D0 (en) | 1999-04-06 | 1999-06-02 | Univ Cambridge Tech | Implantable sensor |
US6285897B1 (en) | 1999-04-07 | 2001-09-04 | Endonetics, Inc. | Remote physiological monitoring system |
US6200265B1 (en) | 1999-04-16 | 2001-03-13 | Medtronic, Inc. | Peripheral memory patch and access method for use with an implantable medical device |
US6669663B1 (en) | 1999-04-30 | 2003-12-30 | Medtronic, Inc. | Closed loop medicament pump |
US6359444B1 (en) | 1999-05-28 | 2002-03-19 | University Of Kentucky Research Foundation | Remote resonant-circuit analyte sensing apparatus with sensing structure and associated method of sensing |
US6546268B1 (en) | 1999-06-02 | 2003-04-08 | Ball Semiconductor, Inc. | Glucose sensor |
US7806886B2 (en) | 1999-06-03 | 2010-10-05 | Medtronic Minimed, Inc. | Apparatus and method for controlling insulin infusion with state variable feedback |
DE19925910B4 (en) | 1999-06-07 | 2005-04-28 | Siemens Ag | Method for processing or processing data |
WO2000077674A1 (en) | 1999-06-10 | 2000-12-21 | Koninklijke Philips Electronics N.V. | Recognition of a useful signal in a measurement signal |
US6423035B1 (en) | 1999-06-18 | 2002-07-23 | Animas Corporation | Infusion pump with a sealed drive mechanism and improved method of occlusion detection |
JP4801301B2 (en) | 1999-06-18 | 2011-10-26 | アボット ダイアベティス ケア インコーポレイテッド | In vivo analyte sensor with limited mass transfer |
US6471689B1 (en) | 1999-08-16 | 2002-10-29 | Thomas Jefferson University | Implantable drug delivery catheter system with capillary interface |
US6923763B1 (en) | 1999-08-23 | 2005-08-02 | University Of Virginia Patent Foundation | Method and apparatus for predicting the risk of hypoglycemia |
US7113821B1 (en) | 1999-08-25 | 2006-09-26 | Johnson & Johnson Consumer Companies, Inc. | Tissue electroperforation for enhanced drug delivery |
US6343225B1 (en) | 1999-09-14 | 2002-01-29 | Implanted Biosystems, Inc. | Implantable glucose sensor |
AT408182B (en) | 1999-09-17 | 2001-09-25 | Schaupp Lukas Dipl Ing Dr Tech | DEVICE FOR VIVO MEASURING SIZES IN LIVING ORGANISMS |
WO2001028416A1 (en) | 1999-09-24 | 2001-04-26 | Healthetech, Inc. | Physiological monitor and associated computation, display and communication unit |
US6478736B1 (en) | 1999-10-08 | 2002-11-12 | Healthetech, Inc. | Integrated calorie management system |
US7317938B2 (en) | 1999-10-08 | 2008-01-08 | Sensys Medical, Inc. | Method of adapting in-vitro models to aid in noninvasive glucose determination |
US6616819B1 (en) | 1999-11-04 | 2003-09-09 | Therasense, Inc. | Small volume in vitro analyte sensor and methods |
US20060091006A1 (en) | 1999-11-04 | 2006-05-04 | Yi Wang | Analyte sensor with insertion monitor, and methods |
AU1607801A (en) | 1999-11-15 | 2001-05-30 | Therasense, Inc. | Transition metal complexes with bidentate ligand having an imidazole ring |
US6291200B1 (en) | 1999-11-17 | 2001-09-18 | Agentase, Llc | Enzyme-containing polymeric sensors |
US6658396B1 (en) | 1999-11-29 | 2003-12-02 | Tang Sharon S | Neural network drug dosage estimation |
US7286894B1 (en) | 2000-01-07 | 2007-10-23 | Pasco Scientific | Hand-held computer device and method for interactive data acquisition, analysis, annotation, and calibration |
JP3449958B2 (en) | 2000-01-18 | 2003-09-22 | 理想科学工業株式会社 | Printing system, printing method, and computer-readable recording medium storing printing program |
US6974437B2 (en) | 2000-01-21 | 2005-12-13 | Medtronic Minimed, Inc. | Microprocessor controlled ambulatory medical apparatus with hand held communication device |
ATE552869T1 (en) | 2000-01-21 | 2012-04-15 | Medtronic Minimed Inc | MICROPROCESSOR-CONTROLLED, AMBULATORY MEDICAL DEVICE WITH HAND-HOLD COMMUNICATION DEVICE |
US7369635B2 (en) | 2000-01-21 | 2008-05-06 | Medtronic Minimed, Inc. | Rapid discrimination preambles and methods for using the same |
WO2001052935A1 (en) | 2000-01-21 | 2001-07-26 | Medical Research Group, Inc. | Ambulatory medical apparatus and method having telemetry modifiable control software |
US7003336B2 (en) | 2000-02-10 | 2006-02-21 | Medtronic Minimed, Inc. | Analyte sensor method of making the same |
US20030060765A1 (en) | 2000-02-16 | 2003-03-27 | Arthur Campbell | Infusion device menu structure and method of using the same |
US6895263B2 (en) | 2000-02-23 | 2005-05-17 | Medtronic Minimed, Inc. | Real time self-adjusting calibration algorithm |
US7890295B2 (en) * | 2000-02-23 | 2011-02-15 | Medtronic Minimed, Inc. | Real time self-adjusting calibration algorithm |
US7027931B1 (en) | 2000-02-24 | 2006-04-11 | Bionostics, Inc. | System for statistical analysis of quality control data |
DZ3338A1 (en) | 2000-03-29 | 2001-10-04 | Univ Virginia | METHOD, SYSTEM AND COMPUTER PROGRAM FOR EVALUATING GLYCEMIC REGULATION OF DIABETES FROM AUTOMATICALLY CONTROLLED DATA |
US6610012B2 (en) | 2000-04-10 | 2003-08-26 | Healthetech, Inc. | System and method for remote pregnancy monitoring |
US6440068B1 (en) | 2000-04-28 | 2002-08-27 | International Business Machines Corporation | Measuring user health as measured by multiple diverse health measurement devices utilizing a personal storage device |
AU2001263022A1 (en) | 2000-05-12 | 2001-11-26 | Therasense, Inc. | Electrodes with multilayer membranes and methods of using and making the electrodes |
US6442413B1 (en) | 2000-05-15 | 2002-08-27 | James H. Silver | Implantable sensor |
US7769420B2 (en) | 2000-05-15 | 2010-08-03 | Silver James H | Sensors for detecting substances indicative of stroke, ischemia, or myocardial infarction |
US7181261B2 (en) | 2000-05-15 | 2007-02-20 | Silver James H | Implantable, retrievable, thrombus minimizing sensors |
US6885883B2 (en) | 2000-05-16 | 2005-04-26 | Cygnus, Inc. | Methods for improving performance and reliability of biosensors |
US7395158B2 (en) | 2000-05-30 | 2008-07-01 | Sensys Medical, Inc. | Method of screening for disorders of glucose metabolism |
CN101385637B (en) | 2000-05-31 | 2011-09-14 | 爱科来株式会社 | Remote data control system and measuring data gathering method |
WO2002017210A2 (en) | 2000-08-18 | 2002-02-28 | Cygnus, Inc. | Formulation and manipulation of databases of analyte and associated values |
WO2002015777A1 (en) | 2000-08-18 | 2002-02-28 | Cygnus, Inc. | Methods and devices for prediction of hypoglycemic events |
US6675030B2 (en) | 2000-08-21 | 2004-01-06 | Euro-Celtique, S.A. | Near infrared blood glucose monitoring system |
AU2001291189A1 (en) | 2000-09-22 | 2002-04-02 | Knobbe, Lim And Buckingham | Method and apparatus for real-time estimation and control of pysiological parameters |
EP1339312B1 (en) | 2000-10-10 | 2006-01-04 | Microchips, Inc. | Microchip reservoir devices using wireless transmission of power and data |
US6695860B1 (en) | 2000-11-13 | 2004-02-24 | Isense Corp. | Transcutaneous sensor insertion device |
US7052483B2 (en) | 2000-12-19 | 2006-05-30 | Animas Corporation | Transcutaneous inserter for low-profile infusion sets |
US20020147135A1 (en) | 2000-12-21 | 2002-10-10 | Oliver Schnell | Method and device for producing an adapted travel treatment plan for administering a medicine in the event of a long-haul journey |
US6560471B1 (en) | 2001-01-02 | 2003-05-06 | Therasense, Inc. | Analyte monitoring device and methods of use |
US6666821B2 (en) | 2001-01-08 | 2003-12-23 | Medtronic, Inc. | Sensor system |
US6970529B2 (en) | 2001-01-16 | 2005-11-29 | International Business Machines Corporation | Unified digital architecture |
US6529752B2 (en) * | 2001-01-17 | 2003-03-04 | David T. Krausman | Sleep disorder breathing event counter |
US20040197846A1 (en) | 2001-01-18 | 2004-10-07 | Linda Hockersmith | Determination of glucose sensitivity and a method to manipulate blood glucose concentration |
BR0206604A (en) | 2001-01-22 | 2004-02-17 | Hoffmann La Roche | Lancet device that has capillary action |
US6721587B2 (en) | 2001-02-15 | 2004-04-13 | Regents Of The University Of California | Membrane and electrode structure for implantable sensor |
US6525330B2 (en) | 2001-02-28 | 2003-02-25 | Home Diagnostics, Inc. | Method of strip insertion detection |
WO2002073503A2 (en) | 2001-03-14 | 2002-09-19 | Baxter International Inc. | Internet based therapy management system |
AU2002247321A1 (en) | 2001-03-14 | 2002-09-24 | Vitaltrak Technology, Inc. | Tracking device |
US6968294B2 (en) | 2001-03-15 | 2005-11-22 | Koninklijke Philips Electronics N.V. | Automatic system for monitoring person requiring care and his/her caretaker |
US7041468B2 (en) | 2001-04-02 | 2006-05-09 | Therasense, Inc. | Blood glucose tracking apparatus and methods |
US6574490B2 (en) | 2001-04-11 | 2003-06-03 | Rio Grande Medical Technologies, Inc. | System for non-invasive measurement of glucose in humans |
US6983176B2 (en) | 2001-04-11 | 2006-01-03 | Rio Grande Medical Technologies, Inc. | Optically similar reference samples and related methods for multivariate calibration models used in optical spectroscopy |
GR1003802B (en) | 2001-04-17 | 2002-02-08 | Micrel �.�.�. ������� ��������� ��������������� ��������� | Tele-medicine system |
US6698269B2 (en) | 2001-04-27 | 2004-03-02 | Oceana Sensor Technologies, Inc. | Transducer in-situ testing apparatus and method |
US6676816B2 (en) | 2001-05-11 | 2004-01-13 | Therasense, Inc. | Transition metal complexes with (pyridyl)imidazole ligands and sensors using said complexes |
US7395214B2 (en) | 2001-05-11 | 2008-07-01 | Craig P Shillingburg | Apparatus, device and method for prescribing, administering and monitoring a treatment regimen for a patient |
US6932894B2 (en) | 2001-05-15 | 2005-08-23 | Therasense, Inc. | Biosensor membranes composed of polymers containing heterocyclic nitrogens |
US7025774B2 (en) | 2001-06-12 | 2006-04-11 | Pelikan Technologies, Inc. | Tissue penetration device |
US7179226B2 (en) | 2001-06-21 | 2007-02-20 | Animas Corporation | System and method for managing diabetes |
EP2319401B1 (en) | 2001-06-22 | 2012-08-22 | Nellcor Puritan Bennett Ireland | Wavelet-based analysis of pulse oximetry signals |
WO2003000127A2 (en) | 2001-06-22 | 2003-01-03 | Cygnus, Inc. | Method for improving the performance of an analyte monitoring system |
US7044911B2 (en) | 2001-06-29 | 2006-05-16 | Philometron, Inc. | Gateway platform for biological monitoring and delivery of therapeutic compounds |
US20030208113A1 (en) | 2001-07-18 | 2003-11-06 | Mault James R | Closed loop glycemic index system |
US6754516B2 (en) | 2001-07-19 | 2004-06-22 | Nellcor Puritan Bennett Incorporated | Nuisance alarm reductions in a physiological monitor |
US20030032874A1 (en) | 2001-07-27 | 2003-02-13 | Dexcom, Inc. | Sensor head for use with implantable devices |
US6702857B2 (en) | 2001-07-27 | 2004-03-09 | Dexcom, Inc. | Membrane for use with implantable devices |
US6544212B2 (en) | 2001-07-31 | 2003-04-08 | Roche Diagnostics Corporation | Diabetes management system |
US6788965B2 (en) | 2001-08-03 | 2004-09-07 | Sensys Medical, Inc. | Intelligent system for detecting errors and determining failure modes in noninvasive measurement of blood and tissue analytes |
WO2003014735A1 (en) | 2001-08-03 | 2003-02-20 | General Hospital Corporation | System, process and diagnostic arrangement establishing and monitoring medication doses for patients |
JP3775263B2 (en) | 2001-08-10 | 2006-05-17 | ニプロ株式会社 | Recording medium and blood glucose measurement system using the recording medium |
US20040142403A1 (en) | 2001-08-13 | 2004-07-22 | Donald Hetzel | Method of screening for disorders of glucose metabolism |
EP1320322A1 (en) | 2001-08-20 | 2003-06-25 | Inverness Medical Limited | Wireless diabetes management devices and methods for using the same |
JP4512363B2 (en) | 2001-08-22 | 2010-07-28 | インストゥルメンテイション ラボラトリー カンパニー | Method and apparatus for calibrating electrochemical sensors |
JP3962250B2 (en) | 2001-08-29 | 2007-08-22 | 株式会社レアメタル | In vivo information detection system and tag device and relay device used therefor |
US6827702B2 (en) | 2001-09-07 | 2004-12-07 | Medtronic Minimed, Inc. | Safety limits for closed-loop infusion pump control |
US6740072B2 (en) | 2001-09-07 | 2004-05-25 | Medtronic Minimed, Inc. | System and method for providing closed loop infusion formulation delivery |
US7052591B2 (en) | 2001-09-21 | 2006-05-30 | Therasense, Inc. | Electrodeposition of redox polymers and co-electrodeposition of enzymes by coordinative crosslinking |
US6830562B2 (en) | 2001-09-27 | 2004-12-14 | Unomedical A/S | Injector device for placing a subcutaneous infusion set |
US20050137480A1 (en) | 2001-10-01 | 2005-06-23 | Eckhard Alt | Remote control of implantable device through medical implant communication service band |
WO2003046695A2 (en) | 2001-11-28 | 2003-06-05 | Phemi Inc. | Methods and apparatus for automated interactive medical management |
US7382405B2 (en) | 2001-12-03 | 2008-06-03 | Nikon Corporation | Electronic apparatus having a user identification function and user identification method |
US7204823B2 (en) | 2001-12-19 | 2007-04-17 | Medtronic Minimed, Inc. | Medication delivery system and monitor |
US7729776B2 (en) | 2001-12-19 | 2010-06-01 | Cardiac Pacemakers, Inc. | Implantable medical device with two or more telemetry systems |
US20050027182A1 (en) | 2001-12-27 | 2005-02-03 | Uzair Siddiqui | System for monitoring physiological characteristics |
US20080255438A1 (en) | 2001-12-27 | 2008-10-16 | Medtronic Minimed, Inc. | System for monitoring physiological characteristics |
US7399277B2 (en) | 2001-12-27 | 2008-07-15 | Medtronic Minimed, Inc. | System for monitoring physiological characteristics |
US7022072B2 (en) | 2001-12-27 | 2006-04-04 | Medtronic Minimed, Inc. | System for monitoring physiological characteristics |
US6980852B2 (en) | 2002-01-25 | 2005-12-27 | Subqiview Inc. | Film barrier dressing for intravascular tissue monitoring system |
US7613491B2 (en) | 2002-05-22 | 2009-11-03 | Dexcom, Inc. | Silicone based membranes for use in implantable glucose sensors |
US8364229B2 (en) | 2003-07-25 | 2013-01-29 | Dexcom, Inc. | Analyte sensors having a signal-to-noise ratio substantially unaffected by non-constant noise |
US8260393B2 (en) | 2003-07-25 | 2012-09-04 | Dexcom, Inc. | Systems and methods for replacing signal data artifacts in a glucose sensor data stream |
US9247901B2 (en) | 2003-08-22 | 2016-02-02 | Dexcom, Inc. | Systems and methods for replacing signal artifacts in a glucose sensor data stream |
US9282925B2 (en) | 2002-02-12 | 2016-03-15 | Dexcom, Inc. | Systems and methods for replacing signal artifacts in a glucose sensor data stream |
US8010174B2 (en) | 2003-08-22 | 2011-08-30 | Dexcom, Inc. | Systems and methods for replacing signal artifacts in a glucose sensor data stream |
EP1487519B1 (en) | 2002-02-26 | 2013-06-12 | TecPharma Licensing AG | Insertion device for an insertion set and method of using the same |
US20030212379A1 (en) | 2002-02-26 | 2003-11-13 | Bylund Adam David | Systems and methods for remotely controlling medication infusion and analyte monitoring |
US6998247B2 (en) | 2002-03-08 | 2006-02-14 | Sensys Medical, Inc. | Method and apparatus using alternative site glucose determinations to calibrate and maintain noninvasive and implantable analyzers |
DE60334365D1 (en) | 2002-03-22 | 2010-11-11 | Animas Technologies Llc | INCREASED PERFORMANCE OF AN ANALYSIS MONITORING DEVICE |
US6936006B2 (en) | 2002-03-22 | 2005-08-30 | Novo Nordisk, A/S | Atraumatic insertion of a subcutaneous device |
GB2388898B (en) | 2002-04-02 | 2005-10-05 | Inverness Medical Ltd | Integrated sample testing meter |
US7027848B2 (en) | 2002-04-04 | 2006-04-11 | Inlight Solutions, Inc. | Apparatus and method for non-invasive spectroscopic measurement of analytes in tissue using a matched reference analyte |
US7410468B2 (en) | 2002-04-19 | 2008-08-12 | Pelikan Technologies, Inc. | Method and apparatus for penetrating tissue |
US7226461B2 (en) | 2002-04-19 | 2007-06-05 | Pelikan Technologies, Inc. | Method and apparatus for a multi-use body fluid sampling device with sterility barrier release |
US7153265B2 (en) | 2002-04-22 | 2006-12-26 | Medtronic Minimed, Inc. | Anti-inflammatory biosensor for reduced biofouling and enhanced sensor performance |
WO2003090614A1 (en) | 2002-04-25 | 2003-11-06 | Matsushita Electric Industrial Co., Ltd. | Dosage determination supporting device, injector, and health management supporting system |
GB2388716B (en) | 2002-05-13 | 2004-10-20 | Splashpower Ltd | Improvements relating to contact-less power transfer |
US7015817B2 (en) | 2002-05-14 | 2006-03-21 | Shuan Michael Copley | Personal tracking device |
US7226978B2 (en) | 2002-05-22 | 2007-06-05 | Dexcom, Inc. | Techniques to improve polyurethane membranes for implantable glucose sensors |
US6865407B2 (en) | 2002-07-11 | 2005-03-08 | Optical Sensors, Inc. | Calibration technique for non-invasive medical devices |
US20040010207A1 (en) | 2002-07-15 | 2004-01-15 | Flaherty J. Christopher | Self-contained, automatic transcutaneous physiologic sensing system |
JP2004054394A (en) | 2002-07-17 | 2004-02-19 | Toshiba Corp | Radio information processing system, radio information recording medium, radio information processor and communication method for radio information processing system |
AU2003302720B9 (en) | 2002-07-19 | 2008-08-21 | Smiths Detection-Pasadena, Inc. | Non-specific sensor array detectors |
WO2004015539A2 (en) | 2002-08-13 | 2004-02-19 | University Of Virginia Patent Foundation | Managing and processing self-monitoring blood glucose |
US6865641B2 (en) | 2002-08-29 | 2005-03-08 | International Business Machines Corporation | Method and apparatus for non-volatile display of information for an electronic device |
US7404796B2 (en) | 2004-03-01 | 2008-07-29 | Becton Dickinson And Company | System for determining insulin dose using carbohydrate to insulin ratio and insulin sensitivity factor |
US7192405B2 (en) | 2002-09-30 | 2007-03-20 | Becton, Dickinson And Company | Integrated lancet and bodily fluid sensor |
US20090177068A1 (en) | 2002-10-09 | 2009-07-09 | Stivoric John M | Method and apparatus for providing derived glucose information utilizing physiological and/or contextual parameters |
JP4599296B2 (en) | 2002-10-11 | 2010-12-15 | ベクトン・ディキンソン・アンド・カンパニー | System and method for initiating and maintaining continuous long-term control of the concentration of a substance in a patient's body using a feedback or model-based controller coupled to a single needle or multi-needle intradermal (ID) delivery device |
US7079977B2 (en) | 2002-10-15 | 2006-07-18 | Medtronic, Inc. | Synchronization and calibration of clocks for a medical device and calibrated clock |
US7381184B2 (en) | 2002-11-05 | 2008-06-03 | Abbott Diabetes Care Inc. | Sensor inserter assembly |
US7572237B2 (en) | 2002-11-06 | 2009-08-11 | Abbott Diabetes Care Inc. | Automatic biological analyte testing meter with integrated lancing device and methods of use |
EP1424637A1 (en) | 2002-11-29 | 2004-06-02 | Instrumentarium Corporation | Artifact removal from an electric signal |
US7009511B2 (en) | 2002-12-17 | 2006-03-07 | Cardiac Pacemakers, Inc. | Repeater device for communications with an implantable medical device |
US7052472B1 (en) | 2002-12-18 | 2006-05-30 | Dsp Diabetes Sentry Products, Inc. | Systems and methods for detecting symptoms of hypoglycemia |
US20040122353A1 (en) | 2002-12-19 | 2004-06-24 | Medtronic Minimed, Inc. | Relay device for transferring information between a sensor system and a fluid delivery system |
US7811231B2 (en) | 2002-12-31 | 2010-10-12 | Abbott Diabetes Care Inc. | Continuous glucose monitoring system and methods of use |
US8771183B2 (en) | 2004-02-17 | 2014-07-08 | Abbott Diabetes Care Inc. | Method and system for providing data communication in continuous glucose monitoring and management system |
US7413749B2 (en) | 2003-03-11 | 2008-08-19 | Purdue Pharma L.P. | Titration dosing regimen for controlled release tramadol |
US9872890B2 (en) | 2003-03-19 | 2018-01-23 | Paul C. Davidson | Determining insulin dosing schedules and carbohydrate-to-insulin ratios in diabetic patients |
US20040199056A1 (en) | 2003-04-03 | 2004-10-07 | International Business Machines Corporation | Body monitoring using local area wireless interfaces |
US7134999B2 (en) | 2003-04-04 | 2006-11-14 | Dexcom, Inc. | Optimized sensor geometry for an implantable glucose sensor |
US20040204868A1 (en) | 2003-04-09 | 2004-10-14 | Maynard John D. | Reduction of errors in non-invasive tissue sampling |
US20050038674A1 (en) * | 2003-04-15 | 2005-02-17 | Braig James R. | System and method for managing a chronic medical condition |
JP2007525241A (en) | 2003-04-18 | 2007-09-06 | インシュレット コーポレイション | User interface for infusion pump remote control and method of use thereof |
US7875293B2 (en) | 2003-05-21 | 2011-01-25 | Dexcom, Inc. | Biointerface membranes incorporating bioactive agents |
US7258673B2 (en) | 2003-06-06 | 2007-08-21 | Lifescan, Inc | Devices, systems and methods for extracting bodily fluid and monitoring an analyte therein |
US8066639B2 (en) | 2003-06-10 | 2011-11-29 | Abbott Diabetes Care Inc. | Glucose measuring device for use in personal area network |
US8460243B2 (en) | 2003-06-10 | 2013-06-11 | Abbott Diabetes Care Inc. | Glucose measuring module and insulin pump combination |
US20040254433A1 (en) | 2003-06-12 | 2004-12-16 | Bandis Steven D. | Sensor introducer system, apparatus and method |
US7155290B2 (en) | 2003-06-23 | 2006-12-26 | Cardiac Pacemakers, Inc. | Secure long-range telemetry for implantable medical device |
US7510564B2 (en) | 2003-06-27 | 2009-03-31 | Abbott Diabetes Care Inc. | Lancing device |
US7722536B2 (en) | 2003-07-15 | 2010-05-25 | Abbott Diabetes Care Inc. | Glucose measuring device integrated into a holster for a personal area network device |
WO2005007223A2 (en) | 2003-07-16 | 2005-01-27 | Sasha John | Programmable medical drug delivery systems and methods for delivery of multiple fluids and concentrations |
US7467003B2 (en) | 2003-12-05 | 2008-12-16 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US8423113B2 (en) | 2003-07-25 | 2013-04-16 | Dexcom, Inc. | Systems and methods for processing sensor data |
JP4708342B2 (en) | 2003-07-25 | 2011-06-22 | デックスコム・インコーポレーテッド | Oxygen augmentation membrane system for use in implantable devices |
US7651596B2 (en) | 2005-04-08 | 2010-01-26 | Dexcom, Inc. | Cellulosic-based interference domain for an analyte sensor |
US8282549B2 (en) | 2003-12-09 | 2012-10-09 | Dexcom, Inc. | Signal processing for continuous analyte sensor |
US20050176136A1 (en) | 2003-11-19 | 2005-08-11 | Dexcom, Inc. | Afinity domain for analyte sensor |
US7108778B2 (en) | 2003-07-25 | 2006-09-19 | Dexcom, Inc. | Electrochemical sensors including electrode systems with increased oxygen generation |
WO2005010756A2 (en) | 2003-07-25 | 2005-02-03 | Philips Intellectual Property & Standards Gmbh | Method and device for monitoring a system |
US20070173709A1 (en) | 2005-04-08 | 2007-07-26 | Petisce James R | Membranes for an analyte sensor |
US7424318B2 (en) | 2003-12-05 | 2008-09-09 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US7366556B2 (en) | 2003-12-05 | 2008-04-29 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
JP2007500336A (en) | 2003-07-25 | 2007-01-11 | デックスコム・インコーポレーテッド | Electrode system for electrochemical sensors |
US7460898B2 (en) | 2003-12-05 | 2008-12-02 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US7761130B2 (en) | 2003-07-25 | 2010-07-20 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US8369919B2 (en) | 2003-08-01 | 2013-02-05 | Dexcom, Inc. | Systems and methods for processing sensor data |
US8845536B2 (en) | 2003-08-01 | 2014-09-30 | Dexcom, Inc. | Transcutaneous analyte sensor |
US9135402B2 (en) | 2007-12-17 | 2015-09-15 | Dexcom, Inc. | Systems and methods for processing sensor data |
US7925321B2 (en) | 2003-08-01 | 2011-04-12 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US8886273B2 (en) | 2003-08-01 | 2014-11-11 | Dexcom, Inc. | Analyte sensor |
US8160669B2 (en) | 2003-08-01 | 2012-04-17 | Dexcom, Inc. | Transcutaneous analyte sensor |
US8676287B2 (en) | 2003-08-01 | 2014-03-18 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US8626257B2 (en) | 2003-08-01 | 2014-01-07 | Dexcom, Inc. | Analyte sensor |
US8275437B2 (en) | 2003-08-01 | 2012-09-25 | Dexcom, Inc. | Transcutaneous analyte sensor |
US7774145B2 (en) | 2003-08-01 | 2010-08-10 | Dexcom, Inc. | Transcutaneous analyte sensor |
US7591801B2 (en) | 2004-02-26 | 2009-09-22 | Dexcom, Inc. | Integrated delivery device for continuous glucose sensor |
US8060173B2 (en) | 2003-08-01 | 2011-11-15 | Dexcom, Inc. | System and methods for processing analyte sensor data |
US6954662B2 (en) | 2003-08-19 | 2005-10-11 | A.D. Integrity Applications, Ltd. | Method of monitoring glucose level |
US7920906B2 (en) | 2005-03-10 | 2011-04-05 | Dexcom, Inc. | System and methods for processing analyte sensor data for sensor calibration |
US8233959B2 (en) * | 2003-08-22 | 2012-07-31 | Dexcom, Inc. | Systems and methods for processing analyte sensor data |
US7148803B2 (en) | 2003-10-24 | 2006-12-12 | Symbol Technologies, Inc. | Radio frequency identification (RFID) based sensor networks |
US20050090607A1 (en) | 2003-10-28 | 2005-04-28 | Dexcom, Inc. | Silicone composition for biocompatible membrane |
WO2005041103A2 (en) | 2003-10-29 | 2005-05-06 | Novo Nordisk A/S | Medical advisory system |
US20050096516A1 (en) | 2003-10-30 | 2005-05-05 | Orhan Soykan | Optical detector of organic analyte |
US6928380B2 (en) | 2003-10-30 | 2005-08-09 | International Business Machines Corporation | Thermal measurements of electronic devices during operation |
US7299082B2 (en) | 2003-10-31 | 2007-11-20 | Abbott Diabetes Care, Inc. | Method of calibrating an analyte-measurement device, and associated methods, devices and systems |
US20090012376A1 (en) | 2003-11-03 | 2009-01-08 | Children's Medical Center Corporation | Continuous Analyte Monitor and Method of Using Same |
WO2005051170A2 (en) | 2003-11-19 | 2005-06-09 | Dexcom, Inc. | Integrated receiver for continuous analyte sensor |
KR100519776B1 (en) | 2003-11-24 | 2005-10-07 | 삼성전자주식회사 | Method and apparatus for converting resolution of video signal |
US20050113886A1 (en) | 2003-11-24 | 2005-05-26 | Fischell David R. | Implantable medical system with long range telemetry |
US20050113648A1 (en) | 2003-11-24 | 2005-05-26 | Soohyun Yang | Bidirectional monitoring system capable of a medical diagnosis and a commercial broadcast |
US8425417B2 (en) | 2003-12-05 | 2013-04-23 | Dexcom, Inc. | Integrated device for continuous in vivo analyte detection and simultaneous control of an infusion device |
US20100185071A1 (en) | 2003-12-05 | 2010-07-22 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US8364231B2 (en) | 2006-10-04 | 2013-01-29 | Dexcom, Inc. | Analyte sensor |
US20080200788A1 (en) | 2006-10-04 | 2008-08-21 | Dexcorn, Inc. | Analyte sensor |
US8423114B2 (en) | 2006-10-04 | 2013-04-16 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US8364230B2 (en) | 2006-10-04 | 2013-01-29 | Dexcom, Inc. | Analyte sensor |
US8287453B2 (en) | 2003-12-05 | 2012-10-16 | Dexcom, Inc. | Analyte sensor |
DE602004029092D1 (en) | 2003-12-05 | 2010-10-21 | Dexcom Inc | CALIBRATION METHODS FOR A CONTINUOUSLY WORKING ANALYTIC SENSOR |
US8425416B2 (en) | 2006-10-04 | 2013-04-23 | Dexcom, Inc. | Analyte sensor |
US8532730B2 (en) | 2006-10-04 | 2013-09-10 | Dexcom, Inc. | Analyte sensor |
US20080197024A1 (en) | 2003-12-05 | 2008-08-21 | Dexcom, Inc. | Analyte sensor |
ES2646312T3 (en) | 2003-12-08 | 2017-12-13 | Dexcom, Inc. | Systems and methods to improve electromechanical analyte sensors |
US7637868B2 (en) | 2004-01-12 | 2009-12-29 | Dexcom, Inc. | Composite material for implantable device |
PL1709750T3 (en) | 2004-01-27 | 2015-03-31 | Altivera L L C | Diagnostic radio frequency identification sensors and applications thereof |
US7580812B2 (en) | 2004-01-28 | 2009-08-25 | Honeywell International Inc. | Trending system and method using window filtering |
US7699964B2 (en) | 2004-02-09 | 2010-04-20 | Abbott Diabetes Care Inc. | Membrane suitable for use in an analyte sensor, analyte sensor, and associated method |
US8165651B2 (en) | 2004-02-09 | 2012-04-24 | Abbott Diabetes Care Inc. | Analyte sensor, and associated system and method employing a catalytic agent |
US7364592B2 (en) | 2004-02-12 | 2008-04-29 | Dexcom, Inc. | Biointerface membrane with macro-and micro-architecture |
US6983884B2 (en) | 2004-02-19 | 2006-01-10 | Neoteric Technology, Limited | Method and apparatus for monitoring transfusion of blood |
US20060154642A1 (en) | 2004-02-20 | 2006-07-13 | Scannell Robert F Jr | Medication & health, environmental, and security monitoring, alert, intervention, information and network system with associated and supporting apparatuses |
JP3590053B1 (en) | 2004-02-24 | 2004-11-17 | 株式会社日立製作所 | Blood glucose measurement device |
US8808228B2 (en) | 2004-02-26 | 2014-08-19 | Dexcom, Inc. | Integrated medicament delivery device for use with continuous analyte sensor |
RU2345705C2 (en) | 2004-02-26 | 2009-02-10 | Диабетес Тулз Сведен Аб | Metabolic control, method and device for obtaining indications about health-determining state of examined person |
US7039538B2 (en) | 2004-03-08 | 2006-05-02 | Nellcor Puritant Bennett Incorporated | Pulse oximeter with separate ensemble averaging for oxygen saturation and heart rate |
GB0405798D0 (en) | 2004-03-15 | 2004-04-21 | E San Ltd | Medical data display |
US7831828B2 (en) | 2004-03-15 | 2010-11-09 | Cardiac Pacemakers, Inc. | System and method for securely authenticating a data exchange session with an implantable medical device |
JP5051767B2 (en) | 2004-03-22 | 2012-10-17 | ボディーメディア インコーポレイテッド | Device for monitoring human condition parameters |
EP1735729A2 (en) | 2004-03-26 | 2006-12-27 | Novo Nordisk A/S | Device for displaying data relevant for a diabetic patient |
US6971274B2 (en) | 2004-04-02 | 2005-12-06 | Sierra Instruments, Inc. | Immersible thermal mass flow meter |
US7815569B2 (en) | 2004-04-21 | 2010-10-19 | University Of Virginia Patent Foundation | Method, system and computer program product for evaluating the accuracy of blood glucose monitoring sensors/devices |
US20050245799A1 (en) | 2004-05-03 | 2005-11-03 | Dexcom, Inc. | Implantable analyte sensor |
US8277713B2 (en) | 2004-05-03 | 2012-10-02 | Dexcom, Inc. | Implantable analyte sensor |
US8792955B2 (en) | 2004-05-03 | 2014-07-29 | Dexcom, Inc. | Transcutaneous analyte sensor |
US7651845B2 (en) | 2004-05-13 | 2010-01-26 | The Regents Of The University Of California | Method and apparatus for glucose control and insulin dosing for diabetics |
US7125382B2 (en) | 2004-05-20 | 2006-10-24 | Digital Angel Corporation | Embedded bio-sensor system |
US6999854B2 (en) | 2004-05-28 | 2006-02-14 | International Business Machines Corporation | Medical infusion pump capable of learning bolus time patterns and providing bolus alerts |
US7118667B2 (en) | 2004-06-02 | 2006-10-10 | Jin Po Lee | Biosensors having improved sample application and uses thereof |
US20060010098A1 (en) | 2004-06-04 | 2006-01-12 | Goodnow Timothy T | Diabetes care host-client architecture and data management system |
US7289855B2 (en) | 2004-06-09 | 2007-10-30 | Medtronic, Inc. | Implantable medical device package antenna |
US7283867B2 (en) | 2004-06-10 | 2007-10-16 | Ndi Medical, Llc | Implantable system and methods for acquisition and processing of electrical signals from muscles and/or nerves and/or central nervous system tissue |
US20070060979A1 (en) | 2004-06-10 | 2007-03-15 | Ndi Medical, Llc | Implantable pulse generator systems and methods for providing functional and / or therapeutic stimulation of muscles and / or nerves and / or central nervous system tissue |
US7623988B2 (en) | 2004-06-23 | 2009-11-24 | Cybiocare Inc. | Method and apparatus for the monitoring of clinical states |
DE102004031092A1 (en) | 2004-06-28 | 2006-01-12 | Giesecke & Devrient Gmbh | transponder unit |
US20060001538A1 (en) | 2004-06-30 | 2006-01-05 | Ulrich Kraft | Methods of monitoring the concentration of an analyte |
US20060001551A1 (en) | 2004-06-30 | 2006-01-05 | Ulrich Kraft | Analyte monitoring system with wireless alarm |
US20060015020A1 (en) | 2004-07-06 | 2006-01-19 | Dexcom, Inc. | Systems and methods for manufacture of an analyte-measuring device including a membrane system |
US8565848B2 (en) | 2004-07-13 | 2013-10-22 | Dexcom, Inc. | Transcutaneous analyte sensor |
US7783333B2 (en) | 2004-07-13 | 2010-08-24 | Dexcom, Inc. | Transcutaneous medical device with variable stiffness |
US7946984B2 (en) | 2004-07-13 | 2011-05-24 | Dexcom, Inc. | Transcutaneous analyte sensor |
WO2006127694A2 (en) | 2004-07-13 | 2006-11-30 | Dexcom, Inc. | Analyte sensor |
US8452368B2 (en) | 2004-07-13 | 2013-05-28 | Dexcom, Inc. | Transcutaneous analyte sensor |
US8886272B2 (en) | 2004-07-13 | 2014-11-11 | Dexcom, Inc. | Analyte sensor |
US20080242961A1 (en) | 2004-07-13 | 2008-10-02 | Dexcom, Inc. | Transcutaneous analyte sensor |
US20060016700A1 (en) | 2004-07-13 | 2006-01-26 | Dexcom, Inc. | Transcutaneous analyte sensor |
EP2329770B2 (en) * | 2004-07-13 | 2024-04-10 | DexCom, Inc. | Transcutaneous analyte sensor |
US7344500B2 (en) | 2004-07-27 | 2008-03-18 | Medtronic Minimed, Inc. | Sensing system with auxiliary display |
US8313433B2 (en) | 2004-08-06 | 2012-11-20 | Medtronic Minimed, Inc. | Medical data management system and process |
CN101091114A (en) | 2004-08-31 | 2007-12-19 | 生命扫描苏格兰有限公司 | Method of manufacturing an auto-calibrating sensor |
EP1799101A4 (en) | 2004-09-02 | 2008-11-19 | Proteus Biomedical Inc | Methods and apparatus for tissue activation and monitoring |
US20080312859A1 (en) | 2004-09-03 | 2008-12-18 | Novo Nordisk A/S | Method of Calibrating a System for Measuring the Concentration of Substances in Body and an Apparatus for Exercising the Method |
US7468033B2 (en) | 2004-09-08 | 2008-12-23 | Medtronic Minimed, Inc. | Blood contacting sensor |
ATE545361T1 (en) | 2004-12-13 | 2012-03-15 | Koninkl Philips Electronics Nv | MOBILE MONITORING |
US20090082693A1 (en) | 2004-12-29 | 2009-03-26 | Therasense, Inc. | Method and apparatus for providing temperature sensor module in a data communication system |
US20070027381A1 (en) | 2005-07-29 | 2007-02-01 | Therasense, Inc. | Inserter and methods of use |
US9398882B2 (en) | 2005-09-30 | 2016-07-26 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte sensor and data processing device |
US7731657B2 (en) | 2005-08-30 | 2010-06-08 | Abbott Diabetes Care Inc. | Analyte sensor introducer and methods of use |
US7883464B2 (en) | 2005-09-30 | 2011-02-08 | Abbott Diabetes Care Inc. | Integrated transmitter unit and sensor introducer mechanism and methods of use |
US8512243B2 (en) | 2005-09-30 | 2013-08-20 | Abbott Diabetes Care Inc. | Integrated introducer and transmitter assembly and methods of use |
EP1835849B1 (en) | 2004-12-29 | 2016-02-17 | LifeScan Scotland Limited | Method of inputting data into an analyte testing device |
US20060166629A1 (en) | 2005-01-24 | 2006-07-27 | Therasense, Inc. | Method and apparatus for providing EMC Class-B compliant RF transmitter for data monitoring an detection systems |
US20060173260A1 (en) | 2005-01-31 | 2006-08-03 | Gmms Ltd | System, device and method for diabetes treatment and monitoring |
US7547281B2 (en) | 2005-02-01 | 2009-06-16 | Medtronic Minimed, Inc. | Algorithm sensor augmented bolus estimator for semi-closed loop infusion system |
US7499002B2 (en) | 2005-02-08 | 2009-03-03 | International Business Machines Corporation | Retractable string interface for stationary and portable devices |
US7545272B2 (en) | 2005-02-08 | 2009-06-09 | Therasense, Inc. | RF tag on test strips, test strip vials and boxes |
AU2006212007A1 (en) | 2005-02-11 | 2006-08-17 | The University Court Of The University Of Glasgow | Sensing device, apparatus and system, and method for operating the same |
KR100638727B1 (en) | 2005-02-28 | 2006-10-30 | 삼성전기주식회사 | Concurrent transceiver for zigbee and bluetooth |
US8133178B2 (en) | 2006-02-22 | 2012-03-13 | Dexcom, Inc. | Analyte sensor |
US20090076360A1 (en) | 2007-09-13 | 2009-03-19 | Dexcom, Inc. | Transcutaneous analyte sensor |
EP1859279A4 (en) | 2005-03-15 | 2009-12-30 | Entelos Inc | Apparatus and method for computer modeling type 1 diabetes |
WO2006102412A2 (en) | 2005-03-21 | 2006-09-28 | Abbott Diabetes Care, Inc. | Method and system for providing integrated medication infusion and analyte monitoring system |
US7889069B2 (en) | 2005-04-01 | 2011-02-15 | Codman & Shurtleff, Inc. | Wireless patient monitoring system |
US20090054753A1 (en) | 2007-08-21 | 2009-02-26 | Mark Ries Robinson | Variable Sampling Interval for Blood Analyte Determinations |
US8060174B2 (en) | 2005-04-15 | 2011-11-15 | Dexcom, Inc. | Analyte sensing biointerface |
GB2425601B (en) | 2005-04-26 | 2008-01-30 | Bio Nano Sensium Technologies | Sensor configuration |
US20060247985A1 (en) | 2005-04-29 | 2006-11-02 | Therasense, Inc. | Method and system for monitoring consumable item usage and providing replenishment thereof |
US8112240B2 (en) | 2005-04-29 | 2012-02-07 | Abbott Diabetes Care Inc. | Method and apparatus for providing leak detection in data monitoring and management systems |
US20060264783A1 (en) | 2005-05-09 | 2006-11-23 | Holmes Elizabeth A | Systems and methods for monitoring pharmacological parameters |
EP1881786B1 (en) | 2005-05-13 | 2017-11-15 | Trustees of Boston University | Fully automated control system for type 1 diabetes |
US7541935B2 (en) | 2005-05-19 | 2009-06-02 | Proacticare Llc | System and methods for monitoring caregiver performance |
US7976466B2 (en) | 2005-06-02 | 2011-07-12 | Isense Corporation | Use of multiple data points and filtering in an analyte sensor |
US20060272652A1 (en) | 2005-06-03 | 2006-12-07 | Medtronic Minimed, Inc. | Virtual patient software system for educating and treating individuals with diabetes |
US20080071580A1 (en) | 2005-06-03 | 2008-03-20 | Marcus Alan O | System and method for medical evaluation and monitoring |
US20070033074A1 (en) | 2005-06-03 | 2007-02-08 | Medtronic Minimed, Inc. | Therapy management system |
EP1893079B1 (en) | 2005-06-08 | 2012-06-27 | SHER, Philip Michael | Fluctuating blood glucose notification threshold profiles and methods of use |
US8251904B2 (en) | 2005-06-09 | 2012-08-28 | Roche Diagnostics Operations, Inc. | Device and method for insulin dosing |
US7413124B2 (en) | 2005-07-19 | 2008-08-19 | 3M Innovative Properties Company | RFID reader supporting one-touch search functionality |
US20070066956A1 (en) | 2005-07-27 | 2007-03-22 | Medtronic Minimed, Inc. | Systems and methods for entering temporary basal rate pattern in an infusion device |
TWI417543B (en) | 2005-08-05 | 2013-12-01 | Bayer Healthcare Llc | Meters and method of using meters having a multi-level user interface with predefined levels of user features |
US20070093786A1 (en) | 2005-08-16 | 2007-04-26 | Medtronic Minimed, Inc. | Watch controller for a medical device |
US20070060869A1 (en) | 2005-08-16 | 2007-03-15 | Tolle Mike C V | Controller device for an infusion pump |
US9089713B2 (en) | 2005-08-31 | 2015-07-28 | Michael Sasha John | Methods and systems for semi-automatic adjustment of medical monitoring and treatment |
US20080314395A1 (en) | 2005-08-31 | 2008-12-25 | Theuniversity Of Virginia Patent Foundation | Accuracy of Continuous Glucose Sensors |
US8965509B2 (en) | 2005-08-31 | 2015-02-24 | Michael Sasha John | Methods and systems for semi-automatic adjustment of medical monitoring and treatment |
EP1921978B1 (en) | 2005-09-09 | 2012-08-01 | F. Hoffmann-La Roche AG | Device and program for diabetes care |
US9072476B2 (en) | 2005-09-23 | 2015-07-07 | Medtronic Minimed, Inc. | Flexible sensor apparatus |
US7756561B2 (en) | 2005-09-30 | 2010-07-13 | Abbott Diabetes Care Inc. | Method and apparatus for providing rechargeable power in data monitoring and management systems |
US20070078314A1 (en) | 2005-09-30 | 2007-04-05 | Grounsell Richard L | System and method for measuring and predicting insulin dosing rates |
US9521968B2 (en) | 2005-09-30 | 2016-12-20 | Abbott Diabetes Care Inc. | Analyte sensor retention mechanism and methods of use |
US7468125B2 (en) | 2005-10-17 | 2008-12-23 | Lifescan, Inc. | System and method of processing a current sample for calculating a glucose concentration |
US20090054747A1 (en) | 2005-10-31 | 2009-02-26 | Abbott Diabetes Care, Inc. | Method and system for providing analyte sensor tester isolation |
US7766829B2 (en) | 2005-11-04 | 2010-08-03 | Abbott Diabetes Care Inc. | Method and system for providing basal profile modification in analyte monitoring and management systems |
EP3064236B1 (en) | 2005-11-08 | 2020-02-05 | Bigfoot Biomedical, Inc. | Method and system for manual and autonomous control of an infusion pump |
US20070173706A1 (en) | 2005-11-11 | 2007-07-26 | Isense Corporation | Method and apparatus for insertion of a sensor |
US20070118030A1 (en) | 2005-11-22 | 2007-05-24 | Isense Corporation | Method and apparatus for analyte data telemetry |
WO2007062173A1 (en) | 2005-11-22 | 2007-05-31 | Vocollect Healthcare Systems, Inc. | Advanced diabetes management system (adms) |
US7963917B2 (en) | 2005-12-05 | 2011-06-21 | Echo Therapeutics, Inc. | System and method for continuous non-invasive glucose monitoring |
US7941200B2 (en) | 2005-12-08 | 2011-05-10 | Roche Diagnostics Operations, Inc. | System and method for determining drug administration information |
US8515518B2 (en) | 2005-12-28 | 2013-08-20 | Abbott Diabetes Care Inc. | Analyte monitoring |
US8160670B2 (en) | 2005-12-28 | 2012-04-17 | Abbott Diabetes Care Inc. | Analyte monitoring: stabilizer for subcutaneous glucose sensor with incorporated antiglycolytic agent |
EP1968432A4 (en) | 2005-12-28 | 2009-10-21 | Abbott Diabetes Care Inc | Medical device insertion |
US7785256B1 (en) | 2006-01-11 | 2010-08-31 | Pacesetter, Inc. | Method and system for displaying patient activity data using Poincaré and intensity plot |
US20070179349A1 (en) | 2006-01-19 | 2007-08-02 | Hoyme Kenneth P | System and method for providing goal-oriented patient management based upon comparative population data analysis |
US7736310B2 (en) | 2006-01-30 | 2010-06-15 | Abbott Diabetes Care Inc. | On-body medical device securement |
US7872574B2 (en) | 2006-02-01 | 2011-01-18 | Innovation Specialists, Llc | Sensory enhancement systems and methods in personal electronic devices |
DE602007013723D1 (en) | 2006-02-09 | 2011-05-19 | Deka Products Lp | SYSTEMS FOR DISPENSING FLUIDS IN PATCH SIZE |
EP1993637A2 (en) | 2006-02-15 | 2008-11-26 | Medingo Ltd. | Systems and methods for sensing analyte and dispensing therapeutic fluid |
AU2007221172A1 (en) | 2006-02-27 | 2007-09-07 | Edwards Lifesciences Corporation | Flux limiting membrane for intravenous amperometric biosensor |
US7826879B2 (en) | 2006-02-28 | 2010-11-02 | Abbott Diabetes Care Inc. | Analyte sensors and methods of use |
US7981034B2 (en) | 2006-02-28 | 2011-07-19 | Abbott Diabetes Care Inc. | Smart messages and alerts for an infusion delivery and management system |
US7885698B2 (en) | 2006-02-28 | 2011-02-08 | Abbott Diabetes Care Inc. | Method and system for providing continuous calibration of implantable analyte sensors |
US8473022B2 (en) | 2008-01-31 | 2013-06-25 | Abbott Diabetes Care Inc. | Analyte sensor with time lag compensation |
US8226891B2 (en) | 2006-03-31 | 2012-07-24 | Abbott Diabetes Care Inc. | Analyte monitoring devices and methods therefor |
US8346335B2 (en) * | 2008-03-28 | 2013-01-01 | Abbott Diabetes Care Inc. | Analyte sensor calibration management |
US7618369B2 (en) | 2006-10-02 | 2009-11-17 | Abbott Diabetes Care Inc. | Method and system for dynamically updating calibration parameters for an analyte sensor |
US8140312B2 (en) | 2007-05-14 | 2012-03-20 | Abbott Diabetes Care Inc. | Method and system for determining analyte levels |
US7620438B2 (en) | 2006-03-31 | 2009-11-17 | Abbott Diabetes Care Inc. | Method and system for powering an electronic device |
US8219173B2 (en) | 2008-09-30 | 2012-07-10 | Abbott Diabetes Care Inc. | Optimizing analyte sensor calibration |
US9392969B2 (en) | 2008-08-31 | 2016-07-19 | Abbott Diabetes Care Inc. | Closed loop control and signal attenuation detection |
US7630748B2 (en) | 2006-10-25 | 2009-12-08 | Abbott Diabetes Care Inc. | Method and system for providing analyte monitoring |
US8374668B1 (en) | 2007-10-23 | 2013-02-12 | Abbott Diabetes Care Inc. | Analyte sensor with lag compensation |
US7653425B2 (en) | 2006-08-09 | 2010-01-26 | Abbott Diabetes Care Inc. | Method and system for providing calibration of an analyte sensor in an analyte monitoring system |
ATE449518T1 (en) | 2006-04-20 | 2009-12-15 | Lifescan Scotland Ltd | METHOD FOR SENDING DATA IN A BLOOD GLUCOSE SYSTEM AND CORRESPONDING BLOOD GLUCOSE SYSTEM |
US8380300B2 (en) | 2006-04-28 | 2013-02-19 | Medtronic, Inc. | Efficacy visualization |
US20070255126A1 (en) | 2006-04-28 | 2007-11-01 | Moberg Sheldon B | Data communication in networked fluid infusion systems |
WO2007128144A1 (en) | 2006-05-10 | 2007-11-15 | F. Hoffmann-La Roche Ag | Infusion apparatus with a data storage device |
US20090054749A1 (en) | 2006-05-31 | 2009-02-26 | Abbott Diabetes Care, Inc. | Method and System for Providing Data Transmission in a Data Management System |
WO2007143225A2 (en) | 2006-06-07 | 2007-12-13 | Abbott Diabetes Care, Inc. | Analyte monitoring system and method |
US7842174B2 (en) | 2006-06-12 | 2010-11-30 | Utah State University | Electrochemical chip with miniaturized sensor array |
US20080177149A1 (en) | 2006-06-16 | 2008-07-24 | Stefan Weinert | System and method for collecting patient information from which diabetes therapy may be determined |
US20080004601A1 (en) | 2006-06-28 | 2008-01-03 | Abbott Diabetes Care, Inc. | Analyte Monitoring and Therapy Management System and Methods Therefor |
US9119582B2 (en) | 2006-06-30 | 2015-09-01 | Abbott Diabetes Care, Inc. | Integrated analyte sensor and infusion device and methods therefor |
US20090105571A1 (en) | 2006-06-30 | 2009-04-23 | Abbott Diabetes Care, Inc. | Method and System for Providing Data Communication in Data Management Systems |
ES2831604T3 (en) | 2006-07-07 | 2021-06-09 | Hoffmann La Roche | Fluid Management Device and Operating Procedures |
CN101489469B (en) | 2006-07-10 | 2012-12-12 | 埃森哲环球服务有限公司 | Mobile personal services platform for providing feedback |
US7908334B2 (en) | 2006-07-21 | 2011-03-15 | Cardiac Pacemakers, Inc. | System and method for addressing implantable devices |
US8932216B2 (en) | 2006-08-07 | 2015-01-13 | Abbott Diabetes Care Inc. | Method and system for providing data management in integrated analyte monitoring and infusion system |
US8206296B2 (en) | 2006-08-07 | 2012-06-26 | Abbott Diabetes Care Inc. | Method and system for providing integrated analyte monitoring and infusion system therapy management |
US9056165B2 (en) | 2006-09-06 | 2015-06-16 | Medtronic Minimed, Inc. | Intelligent therapy recommendation algorithm and method of using the same |
US20090312622A1 (en) | 2006-09-28 | 2009-12-17 | Werner Regittnig | Device And Method For Determining A Value Of A Physiological Parameter Of A Body Fluid |
US8478377B2 (en) | 2006-10-04 | 2013-07-02 | Dexcom, Inc. | Analyte sensor |
US8447376B2 (en) | 2006-10-04 | 2013-05-21 | Dexcom, Inc. | Analyte sensor |
US8449464B2 (en) | 2006-10-04 | 2013-05-28 | Dexcom, Inc. | Analyte sensor |
US8275438B2 (en) | 2006-10-04 | 2012-09-25 | Dexcom, Inc. | Analyte sensor |
US8298142B2 (en) | 2006-10-04 | 2012-10-30 | Dexcom, Inc. | Analyte sensor |
US7831287B2 (en) | 2006-10-04 | 2010-11-09 | Dexcom, Inc. | Dual electrode system for a continuous analyte sensor |
US8562528B2 (en) | 2006-10-04 | 2013-10-22 | Dexcom, Inc. | Analyte sensor |
US8255026B1 (en) | 2006-10-12 | 2012-08-28 | Masimo Corporation, Inc. | Patient monitor capable of monitoring the quality of attached probes and accessories |
US20080092638A1 (en) | 2006-10-19 | 2008-04-24 | Bayer Healthcare Llc | Wireless analyte monitoring system |
EP2106238A4 (en) | 2006-10-26 | 2011-03-09 | Abbott Diabetes Care Inc | Method, system and computer program product for real-time detection of sensitivity decline in analyte sensors |
EP1918837A1 (en) | 2006-10-31 | 2008-05-07 | F. Hoffmann-La Roche AG | Method for processing a chronological sequence of measurements of a time dependent parameter |
US20130324823A1 (en) | 2006-11-20 | 2013-12-05 | Modz Oy | Measurement device, system and method |
FI20065735A0 (en) | 2006-11-20 | 2006-11-20 | Salla Koski | Measurement, monitoring and management system and its constituent equipment |
US20080139910A1 (en) | 2006-12-06 | 2008-06-12 | Metronic Minimed, Inc. | Analyte sensor and method of using the same |
TWI482641B (en) | 2006-12-07 | 2015-05-01 | Daiichi Sankyo Co Ltd | Pharmaceutical composition containing low substituted hydroxypropylcellulose |
WO2008071218A1 (en) | 2006-12-14 | 2008-06-19 | Egomedical Swiss Ag | Monitoring device |
US20080154513A1 (en) | 2006-12-21 | 2008-06-26 | University Of Virginia Patent Foundation | Systems, Methods and Computer Program Codes for Recognition of Patterns of Hyperglycemia and Hypoglycemia, Increased Glucose Variability, and Ineffective Self-Monitoring in Diabetes |
US7946985B2 (en) | 2006-12-29 | 2011-05-24 | Medtronic Minimed, Inc. | Method and system for providing sensor redundancy |
US20080161666A1 (en) | 2006-12-29 | 2008-07-03 | Abbott Diabetes Care, Inc. | Analyte devices and methods |
US7734323B2 (en) | 2007-01-24 | 2010-06-08 | Smiths Medical Asd, Inc. | Correction factor testing using frequent blood glucose input |
US10154804B2 (en) | 2007-01-31 | 2018-12-18 | Medtronic Minimed, Inc. | Model predictive method and system for controlling and supervising insulin infusion |
US9597019B2 (en) | 2007-02-09 | 2017-03-21 | Lifescan, Inc. | Method of ensuring date and time on a test meter is accurate |
US8930203B2 (en) | 2007-02-18 | 2015-01-06 | Abbott Diabetes Care Inc. | Multi-function analyte test device and methods therefor |
US8732188B2 (en) | 2007-02-18 | 2014-05-20 | Abbott Diabetes Care Inc. | Method and system for providing contextual based medication dosage determination |
US7751864B2 (en) | 2007-03-01 | 2010-07-06 | Roche Diagnostics Operations, Inc. | System and method for operating an electrochemical analyte sensor |
US8123686B2 (en) | 2007-03-01 | 2012-02-28 | Abbott Diabetes Care Inc. | Method and apparatus for providing rolling data in communication systems |
US20090093687A1 (en) | 2007-03-08 | 2009-04-09 | Telfort Valery G | Systems and methods for determining a physiological condition using an acoustic monitor |
US8758245B2 (en) | 2007-03-20 | 2014-06-24 | Lifescan, Inc. | Systems and methods for pattern recognition in diabetes management |
US20080234943A1 (en) | 2007-03-20 | 2008-09-25 | Pinaki Ray | Computer program for diabetes management |
EP1972270B1 (en) | 2007-03-23 | 2010-11-03 | Roche Diagnostics GmbH | Method and glucose monitoring system for monitoring individual metabolic response |
US9029157B2 (en) | 2007-04-12 | 2015-05-12 | Nipro Diagnostics, Inc. | Error detection and rejection for a diagnostic testing system |
CA2683721C (en) | 2007-04-14 | 2017-05-23 | Abbott Diabetes Care Inc. | Method and apparatus for providing dynamic multi-stage signal amplification in a medical device |
ES2817503T3 (en) | 2007-04-14 | 2021-04-07 | Abbott Diabetes Care Inc | Procedure and apparatus for providing data processing and control in a medical communication system |
CA2683953C (en) | 2007-04-14 | 2016-08-02 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
CA2683959C (en) | 2007-04-14 | 2017-08-29 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
WO2008128210A1 (en) | 2007-04-14 | 2008-10-23 | Abbott Diabetes Care, Inc. | Method and apparatus for providing data processing and control in medical communication system |
EP2146625B1 (en) | 2007-04-14 | 2019-08-14 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in medical communication system |
US20080269714A1 (en) | 2007-04-25 | 2008-10-30 | Medtronic Minimed, Inc. | Closed loop/semi-closed loop therapy modification system |
US20080269723A1 (en) | 2007-04-25 | 2008-10-30 | Medtronic Minimed, Inc. | Closed loop/semi-closed loop therapy modification system |
CN101715554B (en) | 2007-04-27 | 2013-11-20 | 艾伯特糖尿病护理公司 | No calibration analyte sensors and methods |
US20080278332A1 (en) | 2007-05-08 | 2008-11-13 | Abbott Diabetes Care, Inc. | Analyte monitoring system and methods |
US7928850B2 (en) | 2007-05-08 | 2011-04-19 | Abbott Diabetes Care Inc. | Analyte monitoring system and methods |
US8461985B2 (en) | 2007-05-08 | 2013-06-11 | Abbott Diabetes Care Inc. | Analyte monitoring system and methods |
US10002233B2 (en) | 2007-05-14 | 2018-06-19 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8260558B2 (en) | 2007-05-14 | 2012-09-04 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8103471B2 (en) | 2007-05-14 | 2012-01-24 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US7996158B2 (en) | 2007-05-14 | 2011-08-09 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US20080312845A1 (en) | 2007-05-14 | 2008-12-18 | Abbott Diabetes Care, Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8239166B2 (en) | 2007-05-14 | 2012-08-07 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
EP2156684A4 (en) | 2007-05-14 | 2012-10-24 | Abbott Diabetes Care Inc | Method and apparatus for providing data processing and control in a medical communication system |
US8560038B2 (en) | 2007-05-14 | 2013-10-15 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US9125548B2 (en) | 2007-05-14 | 2015-09-08 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8600681B2 (en) | 2007-05-14 | 2013-12-03 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US8444560B2 (en) | 2007-05-14 | 2013-05-21 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US20080287755A1 (en) | 2007-05-17 | 2008-11-20 | Isense Corporation | Method and apparatus for trend alert calculation and display |
US20080294024A1 (en) | 2007-05-24 | 2008-11-27 | Cosentino Daniel L | Glucose meter system and monitor |
US20080300572A1 (en) | 2007-06-01 | 2008-12-04 | Medtronic Minimed, Inc. | Wireless monitor for a personal medical device system |
WO2008154312A1 (en) | 2007-06-08 | 2008-12-18 | Dexcom, Inc. | Integrated medicament delivery device for use with continuous analyte sensor |
WO2008151452A1 (en) | 2007-06-15 | 2008-12-18 | F. Hoffmann-La Roche Ag | Visualization of a parameter which is measured on the human body |
ES2681895T3 (en) | 2007-06-18 | 2018-09-17 | F. Hoffmann-La Roche Ag | Glucose control method and system to monitor the individual metabolic response and to generate a nutritional response |
US9754078B2 (en) | 2007-06-21 | 2017-09-05 | Immersion Corporation | Haptic health feedback monitoring |
US8617069B2 (en) | 2007-06-21 | 2013-12-31 | Abbott Diabetes Care Inc. | Health monitor |
US8818782B2 (en) | 2007-06-27 | 2014-08-26 | Roche Diagnostics Operations, Inc. | System for developing patient specific therapies based on dynamic modeling of patient physiology and method thereof |
US20090005729A1 (en) | 2007-06-27 | 2009-01-01 | Animas Corporation | Medical infusion pumps |
US8160900B2 (en) | 2007-06-29 | 2012-04-17 | Abbott Diabetes Care Inc. | Analyte monitoring and management device and method to analyze the frequency of user interaction with the device |
EP2170430A2 (en) | 2007-06-29 | 2010-04-07 | Roche Diagnostics GmbH | Method and apparatus for determining and delivering a drug bolus |
US8834366B2 (en) | 2007-07-31 | 2014-09-16 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte sensor calibration |
EP2182838B1 (en) | 2007-07-31 | 2016-05-04 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US7768386B2 (en) | 2007-07-31 | 2010-08-03 | Abbott Diabetes Care Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US20090036760A1 (en) | 2007-07-31 | 2009-02-05 | Abbott Diabetes Care, Inc. | Method and apparatus for providing data processing and control in a medical communication system |
US7731658B2 (en) | 2007-08-16 | 2010-06-08 | Cardiac Pacemakers, Inc. | Glycemic control monitoring using implantable medical device |
US9968742B2 (en) | 2007-08-29 | 2018-05-15 | Medtronic Minimed, Inc. | Combined sensor and infusion set using separated sites |
US9848058B2 (en) | 2007-08-31 | 2017-12-19 | Cardiac Pacemakers, Inc. | Medical data transport over wireless life critical network employing dynamic communication link mapping |
US20090063402A1 (en) | 2007-08-31 | 2009-03-05 | Abbott Diabetes Care, Inc. | Method and System for Providing Medication Level Determination |
CA3105353A1 (en) | 2007-10-10 | 2009-04-16 | Optiscan Biomedical Corporation | Fluid component analysis system and method for glucose monitoring and control |
WO2009049245A1 (en) | 2007-10-11 | 2009-04-16 | Optiscan Biomedical Corporation | Synchronization and configuration of patient monitoring devices |
US8377031B2 (en) | 2007-10-23 | 2013-02-19 | Abbott Diabetes Care Inc. | Closed loop control system with safety parameters and methods |
US8409093B2 (en) | 2007-10-23 | 2013-04-02 | Abbott Diabetes Care Inc. | Assessing measures of glycemic variability |
US8216138B1 (en) | 2007-10-23 | 2012-07-10 | Abbott Diabetes Care Inc. | Correlation of alternative site blood and interstitial fluid glucose concentrations to venous glucose concentration |
US8417312B2 (en) | 2007-10-25 | 2013-04-09 | Dexcom, Inc. | Systems and methods for processing sensor data |
US20090112626A1 (en) | 2007-10-30 | 2009-04-30 | Cary Talbot | Remote wireless monitoring, processing, and communication of patient data |
IL194966A0 (en) | 2007-10-31 | 2009-08-03 | Animas Corp | User interface for insulin infusion device |
US7783442B2 (en) | 2007-10-31 | 2010-08-24 | Medtronic Minimed, Inc. | System and methods for calibrating physiological characteristic sensors |
US8290559B2 (en) | 2007-12-17 | 2012-10-16 | Dexcom, Inc. | Systems and methods for processing sensor data |
US20090164239A1 (en) | 2007-12-19 | 2009-06-25 | Abbott Diabetes Care, Inc. | Dynamic Display Of Glucose Information |
US20090164190A1 (en) | 2007-12-19 | 2009-06-25 | Abbott Diabetes Care, Inc. | Physiological condition simulation device and method |
US20090163855A1 (en) | 2007-12-24 | 2009-06-25 | Medtronic Minimed, Inc. | Infusion system with adaptive user interface |
WO2009097450A1 (en) | 2008-01-30 | 2009-08-06 | Dexcom. Inc. | Continuous cardiac marker sensor system |
EP2090996A1 (en) | 2008-02-16 | 2009-08-19 | Roche Diagnostics GmbH | Medical device |
US20090299156A1 (en) | 2008-02-20 | 2009-12-03 | Dexcom, Inc. | Continuous medicament sensor system for in vivo use |
JP5091881B2 (en) | 2008-02-20 | 2012-12-05 | カルソニックカンセイ株式会社 | Collision detection device |
WO2009105709A1 (en) | 2008-02-21 | 2009-08-27 | Dexcom, Inc. | Systems and methods for processing, transmitting and displaying sensor data |
US8317699B2 (en) | 2008-02-29 | 2012-11-27 | Roche Diagnostics Operations, Inc. | Device and method for assessing blood glucose control |
US20090242399A1 (en) | 2008-03-25 | 2009-10-01 | Dexcom, Inc. | Analyte sensor |
US8396528B2 (en) | 2008-03-25 | 2013-03-12 | Dexcom, Inc. | Analyte sensor |
US8682408B2 (en) | 2008-03-28 | 2014-03-25 | Dexcom, Inc. | Polymer membranes for continuous analyte sensors |
CN102047101A (en) | 2008-03-28 | 2011-05-04 | 德克斯康公司 | Polymer membranes for continuous analyte sensors |
US8583204B2 (en) | 2008-03-28 | 2013-11-12 | Dexcom, Inc. | Polymer membranes for continuous analyte sensors |
US8252229B2 (en) | 2008-04-10 | 2012-08-28 | Abbott Diabetes Care Inc. | Method and system for sterilizing an analyte sensor |
WO2009125421A1 (en) | 2008-04-11 | 2009-10-15 | Indian Institute Of Science | A sub-threshold capfet sensor for sensing analyte, a method and system thereof |
US7783342B2 (en) | 2008-04-21 | 2010-08-24 | International Business Machines Corporation | System and method for inferring disease similarity by shape matching of ECG time series |
US8207860B2 (en) | 2008-04-28 | 2012-06-26 | Medtronic Minimed, Inc. | Automobile physiological monitoring system and method for using the same |
US7938797B2 (en) | 2008-05-05 | 2011-05-10 | Asante Solutions, Inc. | Infusion pump system |
US7826382B2 (en) | 2008-05-30 | 2010-11-02 | Abbott Diabetes Care Inc. | Close proximity communication device and methods |
US8394637B2 (en) | 2008-06-02 | 2013-03-12 | Roche Diagnostics Operations, Inc. | Handheld analyzer for testing a sample |
WO2010009172A1 (en) | 2008-07-14 | 2010-01-21 | Abbott Diabetes Care Inc. | Closed loop control system interface and methods |
US8734422B2 (en) | 2008-08-31 | 2014-05-27 | Abbott Diabetes Care Inc. | Closed loop control with improved alarm functions |
US20100057040A1 (en) | 2008-08-31 | 2010-03-04 | Abbott Diabetes Care, Inc. | Robust Closed Loop Control And Methods |
US9943644B2 (en) | 2008-08-31 | 2018-04-17 | Abbott Diabetes Care Inc. | Closed loop control with reference measurement and methods thereof |
WO2010031059A2 (en) | 2008-09-15 | 2010-03-18 | Deka Products Limited Partnership | Systems and methods for fluid delivery |
US20100095229A1 (en) | 2008-09-18 | 2010-04-15 | Abbott Diabetes Care, Inc. | Graphical user interface for glucose monitoring system |
EP2326944B1 (en) | 2008-09-19 | 2020-08-19 | Dexcom, Inc. | Particle-containing membrane and particulate electrode for analyte sensors |
WO2010035811A1 (en) | 2008-09-29 | 2010-04-01 | テルモ株式会社 | Blood sugar information processor, blood sugar information processing method, and blood sugar information processing program |
US8986208B2 (en) | 2008-09-30 | 2015-03-24 | Abbott Diabetes Care Inc. | Analyte sensor sensitivity attenuation mitigation |
US8287487B2 (en) | 2008-10-15 | 2012-10-16 | Asante Solutions, Inc. | Infusion pump system and methods |
US8597570B2 (en) | 2008-11-04 | 2013-12-03 | Panasonic Corporation | Measurement device, insulin infusion device, measurement method, method for controlling insulin infusion device, and program |
US20100331644A1 (en) | 2008-11-07 | 2010-12-30 | Dexcom, Inc. | Housing for an intravascular sensor |
US9326707B2 (en) | 2008-11-10 | 2016-05-03 | Abbott Diabetes Care Inc. | Alarm characterization for analyte monitoring devices and systems |
US9317657B2 (en) | 2008-11-26 | 2016-04-19 | University Of Virginia Patent Foundation | Method, system, and computer program product for tracking of blood glucose variability in diabetes |
US9320470B2 (en) | 2008-12-31 | 2016-04-26 | Medtronic Minimed, Inc. | Method and/or system for sensor artifact filtering |
US8974439B2 (en) | 2009-01-02 | 2015-03-10 | Asante Solutions, Inc. | Infusion pump system and methods |
EP2394217A4 (en) | 2009-02-04 | 2016-05-04 | Abbott Diabetes Care Inc | Multi-function analyte test device and methods therefor |
US8394246B2 (en) | 2009-02-23 | 2013-03-12 | Roche Diagnostics Operations, Inc. | System and method for the electrochemical measurement of an analyte employing a remote sensor |
DK3912551T3 (en) | 2009-02-26 | 2023-10-30 | Abbott Diabetes Care Inc | Procedure for calibrating an analyte sensor |
US20100249530A1 (en) | 2009-03-24 | 2010-09-30 | Medtronic Minimed, Inc. | Bolus Estimator with Image Capture Device |
US9446194B2 (en) | 2009-03-27 | 2016-09-20 | Dexcom, Inc. | Methods and systems for promoting glucose management |
WO2010121229A1 (en) | 2009-04-16 | 2010-10-21 | Abbott Diabetes Care Inc. | Analyte sensor calibration management |
US9226701B2 (en) | 2009-04-28 | 2016-01-05 | Abbott Diabetes Care Inc. | Error detection in critical repeating data in a wireless sensor system |
EP3925533B1 (en) | 2009-04-30 | 2024-04-10 | DexCom, Inc. | Performance reports associated with continuous sensor data from multiple analysis time periods |
WO2010138874A1 (en) | 2009-05-29 | 2010-12-02 | Abbott Diabetes Care Inc. | Integrated report generation of medical data with varying levels of information |
US8595607B2 (en) | 2009-06-04 | 2013-11-26 | Abbott Diabetes Care Inc. | Method and system for updating a medical device |
US9218453B2 (en) | 2009-06-29 | 2015-12-22 | Roche Diabetes Care, Inc. | Blood glucose management and interface systems and methods |
US20110024043A1 (en) | 2009-07-02 | 2011-02-03 | Dexcom, Inc. | Continuous analyte sensors and methods of making same |
US20110010257A1 (en) | 2009-07-09 | 2011-01-13 | Medtronic Minimed, Inc. | Providing contextually relevant advertisements and e-commerce features in a personal medical device system |
US20110009813A1 (en) | 2009-07-09 | 2011-01-13 | Medtronic Minimed, Inc. | Panning a display of a portable medical device |
CA2778773A1 (en) | 2009-07-13 | 2011-01-20 | Freelance Corporation | Devices, methods, and kits for determining analyte concentrations |
WO2011014851A1 (en) | 2009-07-31 | 2011-02-03 | Abbott Diabetes Care Inc. | Method and apparatus for providing analyte monitoring system calibration accuracy |
US8868151B2 (en) | 2009-08-14 | 2014-10-21 | Bayer Healthcare Llc | Electrochemical impedance spectroscopy enabled continuous glucose monitoring sensor system |
ES2912584T3 (en) | 2009-08-31 | 2022-05-26 | Abbott Diabetes Care Inc | A glucose monitoring system and method |
LT3920471T (en) | 2009-09-08 | 2024-02-26 | Abbott Diabetes Care, Inc. | Methods and articles of manufacture for hosting a safety critical application on an uncontrolled data processing device |
US20110077469A1 (en) | 2009-09-27 | 2011-03-31 | Blocker Richard A | Systems and methods for utilizing prolonged self monitoring in the analysis of chronic ailment treatments |
WO2011041469A1 (en) | 2009-09-29 | 2011-04-07 | Abbott Diabetes Care Inc. | Method and apparatus for providing notification function in analyte monitoring systems |
EP2482724A2 (en) | 2009-09-30 | 2012-08-08 | Dexcom, Inc. | Transcutaneous analyte sensor |
US20110123971A1 (en) | 2009-11-20 | 2011-05-26 | Medivoce, Inc. | Electronic Medical Voice Instruction System |
US9949672B2 (en) | 2009-12-17 | 2018-04-24 | Ascensia Diabetes Care Holdings Ag | Apparatus, systems and methods for determining and displaying pre-event and post-event analyte concentration levels |
US20110163880A1 (en) | 2010-01-07 | 2011-07-07 | Lisa Halff | System and method responsive to an alarm event detected at an insulin delivery device |
US8803688B2 (en) | 2010-01-07 | 2014-08-12 | Lisa Halff | System and method responsive to an event detected at a glucose monitoring device |
CA2728831A1 (en) | 2010-01-22 | 2011-07-22 | Lifescan, Inc. | Diabetes management unit, method, and system |
US9041730B2 (en) | 2010-02-12 | 2015-05-26 | Dexcom, Inc. | Receivers for analyzing and displaying sensor data |
US20110208027A1 (en) | 2010-02-23 | 2011-08-25 | Roche Diagnostics Operations, Inc. | Methods And Systems For Providing Therapeutic Guidelines To A Person Having Diabetes |
WO2011133768A1 (en) | 2010-04-22 | 2011-10-27 | Abbott Diabetes Care Inc. | Devices, systems, and methods related to analyte monitoring and management |
US8726266B2 (en) | 2010-05-24 | 2014-05-13 | Abbott Diabetes Care Inc. | Method and system for updating a medical device |
US8543354B2 (en) | 2010-06-23 | 2013-09-24 | Medtronic Minimed, Inc. | Glucose sensor signal stability analysis |
US9336353B2 (en) | 2010-06-25 | 2016-05-10 | Dexcom, Inc. | Systems and methods for communicating sensor data between communication devices of a glucose monitoring system |
EP4333325A2 (en) | 2010-09-29 | 2024-03-06 | Dexcom, Inc. | Advanced continuous analyte monitoring system |
US9241631B2 (en) | 2010-10-27 | 2016-01-26 | Dexcom, Inc. | Continuous analyte monitor data recording device operable in a blinded mode |
US8657746B2 (en) | 2010-10-28 | 2014-02-25 | Medtronic Minimed, Inc. | Glucose sensor signal purity analysis |
JP6047097B2 (en) | 2010-10-31 | 2016-12-21 | トラスティーズ オブ ボストン ユニバーシティ | Blood glucose control system |
US20120165640A1 (en) | 2010-12-23 | 2012-06-28 | Roche Diagnostics Operations, Inc. | Structured blood glucose testing performed on handheld diabetes management devices |
US8608921B2 (en) | 2011-01-20 | 2013-12-17 | Medtronic Minimed, Inc. | Layered enzyme compositions for use with analyte sensors |
WO2012108939A1 (en) | 2011-02-11 | 2012-08-16 | Abbott Diabetes Care Inc. | Feedback from cloud or hcp to payer or patient via meter or cell phone |
CN103619255B (en) | 2011-02-28 | 2016-11-02 | 雅培糖尿病护理公司 | The device that associates with analyte monitoring device, system and method and combine their device |
EP2685895B1 (en) | 2011-03-17 | 2018-10-10 | University of Newcastle Upon Tyne | System for the self-monitoring and regulation of blood glucose |
US20130035865A1 (en) | 2011-08-05 | 2013-02-07 | Dexcom, Inc. | Systems and methods for detecting glucose level data patterns |
US8710993B2 (en) | 2011-11-23 | 2014-04-29 | Abbott Diabetes Care Inc. | Mitigating single point failure of devices in an analyte monitoring system and methods thereof |
WO2013078426A2 (en) | 2011-11-25 | 2013-05-30 | Abbott Diabetes Care Inc. | Analyte monitoring system and methods of use |
US20130235166A1 (en) | 2012-03-07 | 2013-09-12 | Cambridge Silicon Radio Limited | Synchronisation method |
EP3395252A1 (en) | 2012-08-30 | 2018-10-31 | Abbott Diabetes Care, Inc. | Dropout detection in continuous analyte monitoring data during data excursions |
US9211092B2 (en) | 2013-01-03 | 2015-12-15 | Dexcom, Inc. | End of life detection for analyte sensors |
WO2014145001A1 (en) | 2013-03-15 | 2014-09-18 | Abbott Diabetes Care Inc. | Medical device data processing and communication methods and systems |
EP4151150A1 (en) | 2014-03-30 | 2023-03-22 | Abbott Diabetes Care, Inc. | Method and apparatus for determining meal start and peak events in analyte monitoring systems |
US10664569B2 (en) | 2015-08-21 | 2020-05-26 | Medtronic Minimed, Inc. | Data analytics and generation of recommendations for controlling glycemic outcomes associated with tracked events |
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