WO2010025433A1 - Variable rate closed loop control and methods - Google Patents

Variable rate closed loop control and methods Download PDF

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Publication number
WO2010025433A1
WO2010025433A1 PCT/US2009/055459 US2009055459W WO2010025433A1 WO 2010025433 A1 WO2010025433 A1 WO 2010025433A1 US 2009055459 W US2009055459 W US 2009055459W WO 2010025433 A1 WO2010025433 A1 WO 2010025433A1
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WO
WIPO (PCT)
Prior art keywords
closed loop
loop control
medication delivery
level
delivery rate
Prior art date
Application number
PCT/US2009/055459
Other languages
French (fr)
Inventor
Gary Hayter
Original Assignee
Abbott Diabetes Care Inc.
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Filing date
Publication date
Application filed by Abbott Diabetes Care Inc. filed Critical Abbott Diabetes Care Inc.
Publication of WO2010025433A1 publication Critical patent/WO2010025433A1/en

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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4836Diagnosis combined with treatment in closed-loop systems or methods
    • A61B5/4839Diagnosis combined with treatment in closed-loop systems or methods combined with drug delivery
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0031Implanted circuitry
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532Measuring 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
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1486Measuring 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
    • AHUMAN NECESSITIES
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    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6846Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive
    • A61B5/6847Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive mounted on an invasive device
    • A61B5/6848Needles
    • A61B5/6849Needles in combination with a needle set
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/142Pressure infusion, e.g. using pumps
    • A61M5/14244Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body
    • AHUMAN NECESSITIES
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    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/168Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body
    • A61M5/172Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic
    • A61M5/1723Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic using feedback of body parameters, e.g. blood-sugar, pressure
    • GPHYSICS
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    • G16H20/10ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G16H20/17ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
    • AHUMAN NECESSITIES
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    • AHUMAN NECESSITIES
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    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/142Pressure infusion, e.g. using pumps
    • A61M2005/14208Pressure infusion, e.g. using pumps with a programmable infusion control system, characterised by the infusion program
    • AHUMAN NECESSITIES
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    • A61M2205/00General characteristics of the apparatus
    • A61M2205/35Communication
    • A61M2205/3576Communication with non implanted data transmission devices, e.g. using external transmitter or receiver
    • A61M2205/3592Communication with non implanted data transmission devices, e.g. using external transmitter or receiver using telemetric means, e.g. radio or optical transmission
    • AHUMAN NECESSITIES
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    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M2230/00Measuring parameters of the user
    • A61M2230/20Blood composition characteristics
    • A61M2230/201Glucose concentration
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/142Pressure infusion, e.g. using pumps
    • A61M5/14244Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body
    • A61M5/14276Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body specially adapted for implantation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/50Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests having means for preventing re-use, or for indicating if defective, used, tampered with or unsterile
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Definitions

  • BACKGROUND Benefits of a closed loop control system for treating diabetic conditions with monitoring glucose levels and adjusting delivery rate of insulin are well known.
  • Such systems referred to as artificial pancreas, model healthy pancreas which, when functioning normally, produces insulin (by the beta cells ( ⁇ -cells)) to counteract the rise in glucose levels in the blood stream.
  • beta cells ⁇ -cells
  • Type-1 diabetes mellitus condition exists when the beta cells in the pancreas either die or are unable to produce sufficient amount of insulin naturally in response to the elevated glucose levels.
  • Type-1 diabetes Common treatment of Type-1 diabetes is the use of insulin pumps that are programmed to continuously deliver insulin to the body through an infusion set.
  • insulin pumps to treat Type-2 diabetes (where the beta cells in the pancreas do produce insulin, but an inadequate quantity) is also becoming more prevalent.
  • Such insulin delivery devices are preprogrammed with delivery rates such as basal profiles which are tailored to each user, and configured to provide the needed insulin to the user. Additionally, the preprogrammed delivery rates may be supplemented with periodic administration of bolus dosages of insulin (for example, correction bolus or carbohydrate bolus) as may be needed by the user.
  • continuous glucose monitoring systems have been developed to allow real time monitoring of fluctuation in glucose levels.
  • One example is the FreeStyle Navigator® Continuous Glucose Monitoring System available from Abbott Diabetes Care Inc., of Alameda, California.
  • the use of such glucose monitoring systems provides the user with real time glucose level information.
  • diabetics are able to determine when insulin is needed to lower glucose levels or when additional glucose is needed to raise the level of glucose.
  • closed loop control systems to automate the insulin delivery based on the real time monitoring of the fluctuation in the glucose levels.
  • Closed loop control algorithms such as, for example, proportional, plus integral, plus derivative (PID) control algorithm or model predictive control algorithm exist and are used to control the automatic delivery of insulin based on the glucose levels monitored.
  • PID proportional, plus integral, plus derivative
  • the glucose sensor in the closed loop control system may enter failure mode (permanently or temporarily) in which case the monitored glucose level in the closed loop control system will introduce error and potentially result in undesirable or dangerous amount of insulin being administered.
  • the infusion component in the closed loop control system may have errors or experience failure modes that results in an inaccurate amount of insulin delivered to the user.
  • a method and device for monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determining a variation in the monitored analyte level, determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjusting the closed loop control operation to modify the medication delivery rate frequency.
  • FIG. 1 is a block diagram illustrating an overall closed loop control system in accordance with one embodiment of the present disclosure
  • FIG. 2 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure
  • FIG. 3 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure
  • FIG. 4 is a flowchart illustrating condition deviation monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure
  • FIG. 5 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure
  • FIG. 6 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure
  • FIG. 7 is a flowchart illustrating variable rate control in a closed loop control system in accordance with one embodiment of the present disclosure
  • FIG. 8 is a flowchart illustrating variable rate control in a closed loop control system in accordance with another embodiment of the present disclosure
  • FIGS. 9-10 are flowcharts illustrating blood glucose measurement to improve accuracy of the closed loop control system in accordance with another embodiment of the present disclosure
  • FIG. 11 is a flowchart illustrating medication delivery information to determine analyte sensor condition in a closed loop control system in accordance with one embodiment of the present disclosure.
  • FIG. 12 is a flowchart illustrating detection of false hypoglycemic alarm condition in a closed loop control system in accordance with one embodiment of the present disclosure.
  • embodiments of the present disclosure relate to methods and system for a robust closed loop control system with safety parameters for continuously monitoring at least one analyte such as glucose in body fluid and delivering suitable level of medication such as insulin.
  • the present disclosure relates to the continuous and/or automatic in vivo monitoring of the level of an analyte using an analyte sensor, and under the control of a closed loop control algorithm, determining and delivering an appropriate level of medication such as insulin in response to the monitored analyte level.
  • Embodiments includes medication delivery devices such as external infusion pumps, implantable infusion pumps, on-body patch pump, or any other processor controlled medication delivery devices that are in communication with one or more control units which also control the operation of the analyte monitoring devices.
  • the medication delivery devices may include one or more reservoirs or containers to hold the medication for delivery in fluid connection with an infusion set, for example, including an infusion tubing and/or cannula.
  • the cannula may be positioned so that the medication is delivered to the user or patient at a desired location, such as, for example, in the subcutaneous tissue under the skin layer of the user.
  • 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.
  • an analyte such as glucose, lactate, and the like
  • 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.
  • a sensor (and/or a sensor insertion apparatus) may be, for example, configured to be positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's dermal fluid.
  • continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise.
  • the analyte level may be correlated and/or converted to analyte levels in blood or other fluids.
  • an analyte sensor may be configured to be positioned in contact with dermal 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 through the skin layer and into the dermal layer under the skin surface at a depth of approximately 3 mm under the skin surface and containing dermal 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, months, or longer.
  • 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, the rate of change of the analyte, etc.
  • Predictive alarms may notify the control unit (and/or the user) of predicted analyte levels that may be of concern in advance of the analyte level reaching the future level. This enables the control unit to determine a priori a suitable corrective action and implement such corrective action.
  • FIG. 1 is a block diagram illustrating an overall closed loop control system in accordance with one embodiment of the present disclosure.
  • the closed loop control system 100 includes an insulin delivery unit 120 that is connected to a body 110 of a user or patient to establish a fluid path to deliver medication such as insulin.
  • the insulin delivery unit 120 may include an infusion tubing fluidly connecting the reservoir of the delivery unit 120 to the body 110 using a cannula with a portion thereof positioned in the subcutaneous tissue of the body 110.
  • the system 100 also includes an analyte monitoring device 130 that is configured to monitor the analyte level in the body 110. As shown in FIG. 1, the system 100 also includes an analyte monitoring device 130 that is configured to monitor the analyte level in the body 110. As shown in FIG.
  • a control unit 140 is provided to control the operation of the insulin delivery unit 120 and the analyte monitoring unit 130.
  • the control unit 140 may be a processor based control unit having provided therein one or more closed loop control algorithm to control the operation of the analyte monitoring device 130 and the delivery unit 120.
  • the control unit 140, the analyte monitoring unit 130 and the delivery unit 120 may be integrated in a single housing.
  • the control unit 140 may be provided in the housing of the delivery unit 120 and configured for communication (wireless or wired) with the analyte monitoring unit 130.
  • the control unit may be integrated in the housing of the analyte monitoring unit 130 and configured for communication (wireless or wired) with the delivery unit 120.
  • the control unit 140 may be a separate component of the overall system 100 and configured for communication (wireless or wired) with both the delivery unit 120 and the analyte monitoring unit 130.
  • the analyte monitoring unit 130 may include an analyte sensor that is transcutaneously positioned through a skin layer of the body 110, and in signal communication with a compact data transmitter provided on the skin layer of the body 110 which is configured to transmit the monitored analyte level substantially in real time to the analyte monitoring unit 130 for processing and/or display.
  • the analyte sensor may be wholly implantable in the body 110 with a data transmitter and configured to wirelessly transmit the monitored analyte level to the analyte monitoring unit 130.
  • a data processing device 150 in signal communication with the one or more of the control unit 140, delivery unit 120 and the analyte monitoring unit 130.
  • the data processing device 150 may include an optional or supplemental device in the closed loop control system to provide user input/output functions, data storage and processing.
  • Examples of the data processing device 150 include, but not limited to mobile telephones, personal digital assistants (PDAs), in vitro blood glucose meters, Blackberry® devices, iPhones, Palm® devices, data paging devices, and the like each of which include an output unit such as one or more of a display, audible and/or vibratory output, and/or an input unit such as a keypad, keyboard, input buttons and the like, and which are configured for communication (wired or wireless) to receive and/or transmit data, and further, which include memory devices such as random access memory, read only memory, volatile and/or non- volatile memory that store data.
  • PDAs personal digital assistants
  • in vitro blood glucose meters such as one or more of a display, audible and/or vibratory output
  • an input unit such as a keypad, keyboard, input buttons and the like
  • memory devices such as random access memory, read only memory, volatile and/or non- volatile memory that store data.
  • a data processing terminal 160 which may include a personal computer, a server terminal, a laptop computer a handheld computing device, or other similar computing devices that are configured to data communication (over the internet, local area network (LAN), cellular network and the like) with the one or more of the control unit 140, the delivery unit 120, the analyte monitoring unit 130, or the data processing device 150, to process, analyze, store, archive, and update information.
  • LAN local area network
  • analyte monitoring device 130 of FIG. 1 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, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketones, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid stimulating hormone, and troponin.
  • the concentration of drugs may also be monitored.
  • antibiotics e.g., gentamicin, vancomycin, and the like
  • digitoxin digoxin
  • digoxin drugs of abuse
  • theophylline drugs of abuse
  • warfarin drugs of abuse
  • each of the components shown in the system 100 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, for example, by exchanging or pre-storing and/or verifying unique device identifiers as part of communication between the devices, by using periodic keep alive signals, or configuration of one or more devices or units in the overall system as a master-slave arrangement with periodic bi-directional communication to confirm integrity of signal communication therebetween.
  • data communication may be encrypted or encoded (and subsequently decoded by the device or unit receiving the data), or transmitted using public-private keys, to ensure integrity of data exchange.
  • error detection and/or correction using, for example, cyclic redundancy check (CRC) or techniques may be used to detect and/or correct for errors in signals received and/or transmitted between the devices or units in the system 100.
  • data communication may be responsive to a command or data request received from another device in the system 100, while some aspects of the overall system 100 may be configured to periodically transmit data without prompting (such as the data transmitter, for example, in the analyte monitoring unit 130 periodically transmitting analyte related signals.
  • the communication between the devices or units in the system 100 may include one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an
  • data processing device 150 analyte monitoring unit
  • the housing of these devices may include a strip port to receive a blood glucose test strip with blood sample to determine the blood glucose level.
  • a user input device such as an input button or keypad may be provided to manually enter such information.
  • the result may be wirelessly and/or automatically transmitted to another device in the system 100. For example, it is desirable to maintain a certain level of water tight seal on the housing of the delivery unit 120 during continuous use by the patient or user. In such case, incorporating a strip port to receive a blood glucose test strip may be undesirable.
  • the blood glucose meter function including the strip port may be integrated in the housing of another one of the devices or units in the system (such as in the analyte monitoring unit 103 and/or data processing device 150).
  • the result from the blood glucose test, upon completion may be wirelessly transmitted to the delivery unit 120 for storage and further processing.
  • test strip 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® or Precision® 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.
  • the information may be used to calibrate the analyte sensor, confirm results of the sensor to increase the confidence in the accuracy level thereof (e.g., in instances in which information obtained by sensor is employed in therapy related decisions), determine suitable amount of bolus dosage for administration by the delivery unit 120.
  • 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 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.
  • One or more devices or components of the system 100 may include an alarm system that, e.g., based on information from control unit 140, 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 reaches or exceeds a threshold rate of change or acceleration.
  • 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 reaches or exceeds a threshold rate of change or acceleration.
  • 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.
  • alarms may be associated with occlusion conditions, low reservoir conditions, malfunction or anomaly in the fluid delivery and the like. System alarms may also 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. Referring yet again to FIG.
  • the control unit 140 of the closed loop control system 100 may include one or more processors such as microprocessors and/or application specific integrated circuits (ASIC), volatile and/or non-volatile memory devices, and additional components that are configured to store and execute one or more closed loop control algorithms to dynamically control the operation of the delivery unit 120 and the analyte monitoring unit 130.
  • the one or more closed loop control algorithms may be stored as a set of instructions in the one or more memory devices and executed by the one or more processors to vary the insulin delivery level based on, for example, glucose level information received from the analyte sensor.
  • the one or more control algorithms of the control unit 140 are configured to monitor parameters and conditions associated with a safety indication of the closed loop control system 100 and generate and notify the user, as may be desirable to perform one or more troubleshooting actions and/or automatically revert to a semi-closed loop control mode or a manual control mode that require some level of user, patient or healthcare provider intervention.
  • FIG. 2 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure.
  • control unit 140 executing the closed loop system control is configured to monitor the closed loop control operation parameters (210).
  • the closed loop control operation parameters may be associated with the operation of the delivery unit 120, and operational conditions associated therewith such as fluid delivery, amount of insulin delivered, potential occlusion and the like.
  • the closed loop control operation parameters monitored may also include operational conditions associated with the analyte monitoring unit 130 such as, for example, the validity or integrity of analyte sensor signals, unanticipated sensor signal drop out, missing sensor data, and the like.
  • monitored control operation parameters may include the integrity of the communication connection between the devices or units in the system 100.
  • an adverse condition associated with a safety state of the closed loop operation is detected (220), it is determined whether the detected adverse condition exceeds a preset safety level (230).
  • a preset safety level For example, in the case where the adverse condition is associated with the integrity of analyte sensor signals, it is determined whether sufficiently accurate glucose level can be derived based on the received sensor signals (for example, based on extrapolation using previously received sensor data, and/or in conjunction with a rate of change of glucose level determination).
  • the adverse condition detected may also include a determined medication delivery level that exceeds a preset threshold level (for example, a physician determined maximum basal delivery rate for the user).
  • the adverse condition detected may include communication failure between the components of the overall system
  • the 100 including, the analyte monitoring unit 130 and the delivery unit 120.
  • control unit 140 when it is determined that the detected adverse condition does not exceed a preset safety level, in one aspect, the control unit 140 is configured to proceed with the execution of the closed loop control algorithm to based on the real time glucose data received from the analyte monitoring unit 130 to adjust the insulin delivery rate from the delivery unit 120, and the routine returns to monitoring the closed loop operation parameters.
  • the control unit 140 in one embodiment is configured to command or instruct the delivery unit 120 to revert to a non-zero pre-programmed closed loop operation state within the safety level (240).
  • control unit 140 when it is determined that the determined insulin level for delivery exceeds the safety level or maximum delivery rate (for example, established by a physician or healthcare provider, or the user, and programmed and stored in the control unit 140), the control unit 140 is configured to automatically revert to an insulin delivery rate that is within the safety level so that potential overdosing may be avoided.
  • the safety level or maximum delivery rate for example, established by a physician or healthcare provider, or the user, and programmed and stored in the control unit 140
  • the control unit 140 is configured to automatically revert to an insulin delivery rate that is within the safety level so that potential overdosing may be avoided.
  • control unit 140 may be configured to issue a command to the delivery unit 120 every 15 minutes (or some other predetermined time interval) which sets insulin delivery rate for a 20 minute time period (or some other suitable time period).
  • the control unit 140 is configured to instruct the delivery unit 120 to revert to a pre-programmed delivery rate that is within the safety level (for example, a less amount of insulin to be delivered).
  • the detected adverse condition may include a determination of insulin on board value that, in conjunction with the insulin amount to be delivered exceeds the upper safely level of insulin delivery, the control unit 140 may be configured to revert to or switch to a preset or pre-programmed level that would bring the insulin delivery amount to be within the determined safety level.
  • the insulin delivery amount that is within the safety level may be pre-programmed in the control unit 140, for example, and implemented as part of the closed loop control to automatically deliver the insulin amount based on the pre-programmed level.
  • the control unit 140 may be configured to modify or adjust the existing insulin delivery rate that is within the safety level in response to the detected adverse condition, (for example, reducing the determined insulin delivery rate by a certain factor such as 75%, to maintain the insulin delivery amount within the safety level).
  • the control unit 140 may be configured to operate within a predefined safety range rather than requesting user intervention or disabling the closed loop control operation to revert to a manual control operation mode. While certain examples of adverse conditions are discussed above, within the scope of the present disclosure, any other condition associated with the safety level in the operation of the closed loop control system 100 are contemplated, the detection of any of which initiates the evaluation of the detected condition and appropriate modification to the closed loop control system parameters to continue operation of the closed loop control operation without prematurely disabling the system, while maintaining the desired level of safety in using the closed loop control system 100.
  • FIG. 3 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure.
  • control unit 140 retrieves a preset safety level information (310) and compares the retrieved preset safety level information to one or more detected adverse condition (320). Thereafter, a level of severity associated with the detected adverse condition is determined based, at least in part on the retrieved preset safety level information (330). After determining the severity level, the control unit 140 is configured to generate one or more closed loop operation instructions based on the determined severity level for execution.
  • control unit 140 when an adverse condition is detected by the control unit 140, the control unit 140 (FIG. 1) is configured in one aspect to determine how severe is the detected adverse condition with respect to the automated insulin delivery. For example, control unit 140 may detect a communication failure from the transmitter of the analyte monitoring unit 130 and thus not receive a current sensor data indicative of the glucose level. However, the control unit 140 may have stored in one or more of its memory units previously received glucose levels from the transmitter of the analyte monitoring unit 130. Given an insulin delivery rate that is within the safety level, and a relatively stable glucose value (for example, based on a rate of change of glucose determination from previously received glucose data), the control unit 140 may be configured to declare the communication failure as a non- critical adverse condition detected. In this manner, the generated closed loop operation instruction (340) may not modify the current delivery rate by the delivery unit 120 (FIG. 1).
  • the generated closed loop operation instruction (340) may include commands to the delivery unit 120 (FIG. 1) to modify the delivery rate and/or revert to a preprogrammed delivery rate that are within the previously determined safety level.
  • the control unit 140 (FIG. 1) may be configured to continuously monitor the presence of the detected adverse condition until the condition is corrected, in which case, the generated closed loop operation instruction (340) may include commands to the delivery unit 120 to return to the prior closed loop control operation.
  • control unit 140 monitors the closed loop operation parameters (410) and when it detects one or more monitored closed loop operation parameters deviating from a predetermined level
  • control unit 140 may be configured to generate and output a request for confirmation of the detected deviation of the monitored closed loop operation parameter (430).
  • a user interface such as a display unit or audible/vibratory notification in the insulin delivery unit 120 and/or the analyte monitoring unit 130 may indicate a notification for the user to confirm the presence of the detected deviation of the monitored closed loop operation parameter.
  • the control unit 140 may be configured to modify the closed loop control operation based on the detected deviation of one or more of its parameters (450).
  • the control unit 140 may be configured to disable the closed loop control operation, and initiate a manual operation mode (460) to deliver insulin by the delivery unit 120 (FIG. 1).
  • control unit 140 may be configured to request for user confirmation or verification of the presence of the detected adverse condition prior to initiating responsive corrective action, and further, when no verification or confirmation is received, for example, within a set time period, the control unit 140 (FIG. 1) may be configured to disable the closed loop control operation. Accordingly, certain adverse conditions detected may prompt the control unit 140 (FIG. 1) to request confirmation prior to automatically responding to such occurrence of adverse condition, and further, when no confirmation is received, the control unit 140 (FIG. 1) may temporarily revert to a semi-closed loop or non-closed loop manual delivery mode.
  • control unit 140 may automatically, temporarily adjust the delivery mode of the delivery unit 120 (FIG. 1), or alternatively, require user intervention.
  • any parameter or condition associated with the operation of the closed loop control system 100 are contemplated including but not limited to, analyte sensor operation, sensor signal filtering, sensor signal level, sensor calibration, sensor signal attenuation, communication failure, signal outlier condition, rate of change of the glucose level, insulin delivery rate, insulin on board information, type of insulin, duration of the closed loop control operation, number or frequency of bolus dosage administration, predicted or projected glucose level and/or the direction of the predicted or projected glucose level, frequency of blood glucose measurements, maximum or minimum insulin delivery level, for example.
  • FIG. 5 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure.
  • control unit 140 in one embodiment, controls unit 140
  • FIG. 1 is configured to monitor closed loop operation parameters (510) in the closed loop control system 100 (FIG. 1).
  • the control unit 140 is configured to retrieve and execute a preprogrammed delivery rate (530) (for example, a predetermined basal profile), while maintaining the closed loop control operation mode.
  • the control unit 140 is configured to generate and output instructions or request to confirm and/or correct the detected potential fault or failure mode of the analyte sensor (540).
  • the closed loop control operation is not disabled when it is initially detected that the analyte sensor may not be properly functioning. Rather, the closed loop control operation includes the execution of a pre-programmed delivery rate that is determined to be within a safety level, and when the potential fault condition or failure mode has been corrected, the control unit 140 may be configured to terminate the execution of the pre-programmed delivery rate and resume real time automatic adjustment to the insulin delivery rate based on the analyte sensor signals.
  • the control unit 140 is configured to instruct the delivery unit 120 to execute a predetermined delivery rate that is within the safety level until corrective action related to the analyte sensor (for example, replacing the sensor, or recalibrating the sensor with a blood glucose measurement) is performed.
  • the control unit 140 may be configured to modify the retrieved predetermined delivery rate based on the insulin delivered (for example, to consider the insulin on board level) so that the safety level associated with the amount of insulin to be delivered is maintained.
  • FIG. 6 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure.
  • the control unit 140 receives analyte sensor operation information (610)
  • one or more routines are performed to confirm the proper operation of the analyte sensor (620).
  • the control unit 140 may be configured to verify the calibration information of the analyte sensor so that the value level derived therefrom accurately indicates the monitored glucose level.
  • control unit 140 may be configured to retrieve the most recent sensor sensitivity determination based, for example, on the reference blood glucose measurement received, and to compare the retrieved sensitivity to a stored nominal sensitivity for the sensor to confirm a variation between sensitivities not exceeding a predetermined level.
  • the current blood glucose measurement is used to determine an updated sensor sensitivity value which may be used in conjunction with one or more prior sensitivity values or nominal sensitivity value. Referring back to FIG. 6, when it is confirmed that the analyte sensor is in proper operation mode, the preprogrammed delivery rate executed by the delivery unit 120 (FIG.
  • the operation of the closed loop control system 100 may include monitoring the condition or parameters associated with the analyte monitoring unit 130 and for example, the analyte sensor, and execute one or more routines to instruct the delivery unit 120 to temporarily execute preprogrammed or modified delivery profile determined to be within the safety limits, or to disable the closed loop control operation to maintain the desired degree of safety in using the closed loop control system 100 (FIG. 1).
  • FIG. 7 is a flowchart illustrating variable rate control in a closed loop control system in accordance with one embodiment of the present disclosure.
  • control unit 140 executing the closed loop control algorithm in the closed loop control system 100 receives monitored analyte level at a predetermined frequency (710).
  • the analyte variation level is determined (720). Thereafter, as shown, the medication delivery rate adjustment frequency is determined based on the determined analyte variation level (730), and thereafter, the delivery unit 120 (FIG. 1) is instructed to deliver the medication at the determined medication delivery rate adjustment frequency (740). That is, in one aspect, the rate of monitored glucose level is associated with the adjustment of the frequency in which to instruct the delivery unit 120 to deliver insulin.
  • control unit 140 may be configured to monitor the glucose level from the analyte monitoring unit 130 at a higher frequency (such as, for example once per minute), and also, adjust the rate of insulin delivery by the delivery unit 120 (FIG. 1) at a lower frequency (for example, once every 15 minutes).
  • control unit 140 may be configured to issue an instruction or command to the delivery unit 120 once every 15 minutes (or some other suitable interval) to vary the delivery rate based on the glucose level.
  • control unit 140 is configured to monitor the variation in the glucose level monitored, and as long as the variation is within a threshold level, the corresponding insulin level delivery adjustment determination is not executed with the same or similar frequency.
  • the rate of insulin delivery may be more frequent (for example, adjustment to the delivery rate once every 5 minutes rather than 15 minutes, or with each determination of the glucose level).
  • the frequency of the adjustment may be associated with the monitored glucose level such that, for example, control unit 140 may be configured to determine, with each received glucose value, whether adjustment to the insulin delivery rate is needed.
  • FIG. 8 is a flowchart illustrating variable rate control in a closed loop control system in accordance with another embodiment of the present disclosure.
  • control unit 140 in one aspect may be configured to instruct the delivery unit 120 (FIG. 1) to deliver medication based on closed loop control parameters at a first delivery rate adjustment frequency (810). Thereafter, the analyte variation level is determined based on the monitored analyte level at a predetermined frequency (820).
  • condition information for example, but not limited to an anticipated meal event
  • a second delivery rate adjustment frequency is determined based on the analyte level variation and/or received condition information (840), and the medication delivery is executed (for example, by the insulin delivery unit 120 (FIG. I)) at the determined second delivery rate adjustment frequency (850).
  • control unit 140 is configured to maximize responsiveness to substantial variation in monitored glucose level, or in anticipation of variation in glucose level, while providing lower power requirements for the various components of the system 100 (FIG. 1).
  • other suitable time intervals or frequency may be used for the glucose monitoring, and further, the associated adjustment to the insulin delivery rate. That is, embodiments of the present disclosure allow for lower rate of control commands, for example, where the delivery unit 120 and the analyte monitoring unit 130 are configured in the system 100 as separate components, with the control unit 140 provided with the analyte monitoring unit 130 and communicating wirelessly with the delivery unit 120, and each being powered by a respective power supply such as a battery.
  • FIGS. 9-10 are flowcharts illustrating blood glucose measurement to improve accuracy of the closed loop control system in accordance with another embodiment of the present disclosure.
  • closed loop operation parameters are monitored (910) and when onset of medication delivery level (for example, a large insulin dosage level) that exceeds a predetermined threshold level is detected (920) a blood glucose measurement information is received (930) (for example, from a blood glucose meter or manually entered by user input). Based on the received blood glucose measurement information, it is determined whether the received blood glucose measurement is within a predetermined margin of error to a time corresponding analyte sensor data (940). In other words, it is determined whether the sensor data correlates to the blood glucose measurement within a predetermined margin of error.
  • the analyte sensor data and the blood glucose measurement are within the predetermined margin of error, then the detected onset of medication delivery level is maintained and the delivery unit 120 delivers that level of medication (950).
  • the blood glucose measurement received is not within the predetermined margin of error (940)
  • the closed loop control parameters associated with the analyte monitoring and/or the medication delivery are retrieved (1010), and the retrieved closed loop control parameters are evaluated based on the received blood glucose measurement (1020).
  • one or more of the closed loop control parameters retrieved may include a request for an additional blood glucose measurement value, an instruction to modify or adjust insulin delivery rate, command to disable closed loop control operation and initiate semi-closed loop control operation or manual control operation, or instruction to recalibrate the analyte sensor, among others.
  • the retrieved one or more parameters may be modified (1030) and thereafter the modified one or more closed loop control parameters is stored (1040).
  • the control unit 140 may prompt the user to enter a current blood glucose measurement (for example, using an in vitro blood glucose meter), to confirm and/or verify the accuracy of the analyte sensor level from the analyte monitoring unit 130 based on which the large amount of insulin to be delivered was determined for execution.
  • a Kalman filter may be used as part of the control unit 140 to process the analyte sensor data and the received blood glucose measurement to optimally adjust the insulin level.
  • the request or prompt to enter the blood glucose measurement may be initiated when the determined insulin amount for delivery in the closed loop control system 100 exceeds a predetermined safety level established, for example, by a healthcare provider or physician, where the safety level includes, for example, the highest insulin delivery rate without blood glucose measurement confirmation.
  • a predetermined safety level established, for example, by a healthcare provider or physician
  • the safety level includes, for example, the highest insulin delivery rate without blood glucose measurement confirmation.
  • other conditions or parameters may be used to trigger the request for blood glucose measurement for confirming sensor accuracy, glucose level verification, and the like.
  • the control unit 140 may be configured to discontinue requesting blood glucose measurements (even when the insulin level to be delivered exceeds the predetermined safety level) when a predetermined number of successful blood glucose measurement confirmations have occurred and the analyte sensor is considered accurate and stable.
  • FIG. 11 is a flowchart illustrating medication delivery information to determine analyte sensor condition in a closed loop control system in accordance with one embodiment of the present disclosure.
  • control unit 140 in the closed loop control operation state of the closed loop control system 100, monitors closed loop operation parameters (1110) and performs a predictive modeling analysis of the monitored closed loop control operation parameters associated with the medication delivery and analyte sensor to determine a predictive glucose response (1120).
  • the determined predictive glucose response is compared with the corresponding monitored analyte sensor signal (1130) and a sensor signal condition based on the comparison is determined (1140).
  • the sensor signal condition may indicate a signal attenuation condition of the glucose sensor.
  • the robustness of the closed loop control system 100 may be enhanced and accuracy of the overall system 100 improved.
  • the predictive model used may include a routine or algorithm that describes glucose response or behavior based on one or more exogenous factors including, among others, insulin delivery information, meal intake, exercise events, and the like, as well as prior monitored sensor data.
  • real time insulin delivery information may be used to improve glucose sensor anomalies such as signal dropouts and early signal attenuation.
  • control unit 140 may determine, based on the comparison that sensor signal dropout or early signal attenuation is detected, and thus may prompt the user to enter a reference blood glucose measurement value.
  • certain alarm or notification functions related to the monitored analyte level such as hypoglycemic alarm, output display of glucose values in real time, may be modified or disabled given the detected anomaly with the sensor signal.
  • other variables may be compared based on the predictive model and the actual measured sensor signal such as, for example, rate of change of the glucose level determined based on the actual measured values from the sensor and compared with the modeled rate of change information.
  • operations of the analyte monitoring unit 130 may be adjusted accordingly, for example, to mitigate or address the signal abnormality. For example, when such sensor signal condition indicates adverse signal condition at the time of scheduled sensor calibration, the calibration attempt may be disqualified and the user may be instructed to perform another calibration or to delay the calibration until the sensor signal has stabilized and the indicated adverse signal condition is no longer present.
  • condition associated with hypoglycemic state is detected (1220) based on monitored closed loop operation parameters (1210) by, for example, the control unit 140 (FIG. 1).
  • a pre-hypoglycemic condition notification routine is performed (1230). If the hypoglycemic state or condition is confirmed (1240), then a corresponding notification such as a hypoglycemic alarm is output (1250), and the closed loop control parameters are accordingly updated to take into account of the detected hypoglycemic condition (1260).
  • the routine returns to monitor the closed loop operation parameters (1210). That is, in one aspect, when a condition associated with hypoglycemia is detected, the control unit 140 may be configured to confirm the presence of the detected hypoglycemic state before asserting an alarm notification, for example, to the user. In this manner, potential false hypoglycemic alarms are minimized based on, for example, presence of glucose sensor signal dropout or early signal attenuation or other sensor anomaly state that indicates a false low glucose level.
  • hypoglycemic alarms or notifications are provided with sensor signal dropout tolerance levels. More specifically, based on the medication delivery rate information, and other parameters associated with the closed loop control operation, the control unit 140 may be configured to determine a degree or level of uncertainly in the measured sensor signal based on the predicted or anticipated glucose level derived, for example, based on the parameters associated with the closed loop control algorithm, including, such as amount of insulin delivered, insulin on board information, glucose rate of change information, among others.
  • control unit 140 may be configured to confirm the presence of the hypoglycemic condition, by for example, requiring additional sensor data to be received and analyzed and determining that the sensor signals indicate a persistent low glucose value. In this manner, the rather than asserting the hypoglycemic condition notification immediately upon detection of a sensor signal level below the alarm threshold, control unit 140 in one aspect is configured to confirm the presence of the hypoglycemic condition, and upon confirmation, to assert the alarm or notification associated with the hypoglycemic condition.
  • control unit 140 may be configured to initiate and execute a sensor signal dropout detection algorithm to determine whether the detected potential hypoglycemic condition is associated with sensor signal dropout or attributable to low glucose level.
  • control unit 140 may be configured to assert an alert notification (associated with less urgency or criticality), and if the potential hypoglycemic condition is confirmed, to assert the hypoglycemic condition alarm.
  • the alert notification may include a single audible beep that does not repeat. If the glucose is persistently below the hypoglycemic threshold (or alarm condition level), or below a lower safety threshold, the notification may be escalated to an alarm, for example, with three consecutive audible beeps with or without repeat routines.
  • a robust closed loop control system includes safety checks and verifications to address potential errors and/or anomalies in detected or monitored conditions and/or parameters enhancing the accuracy and confidence level of the closed loop control operation in the treatment of diabetic conditions.
  • a method in accordance with one embodiment includes monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determining a variation in the monitored analyte level, determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjusting the closed loop control operation to modify the medication delivery rate frequency.
  • the predetermined frequency associated with the monitored signals the analyte sensor may be greater than the medication delivery rate frequency.
  • the analyte sensor in one embodiment includes a glucose sensor.
  • the modification to the medication delivery rate frequency may be performed dynamically based in part on the determined variation in the monitored analyte level.
  • the closed loop control operation may be adjusted to modify the medication delivery rate frequency based on one or more of anticipated carbohydrate intake, anticipated exercise event, or anticipated change in the physiological condition. In another aspect, adjusting the closed loop control operation to modify the medication delivery rate frequency may be performed to minimize power consumption level associated with medication delivery.
  • the medication may include one or more of insulin or glucagon.
  • the variation in the monitored analyte level may be associated with a carbohydrate intake event.
  • a device in accordance with another embodiment includes one or more processors, and a memory operatively coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to monitor a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determine a variation in the monitored analyte level, determine a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjust the closed loop control operation to modify the medication delivery rate frequency.
  • the predetermined frequency associated with the monitored signals of the analyte sensor is greater than the medication delivery rate frequency.
  • the analyte sensor in a further embodiment includes a glucose sensor.
  • the medication may include one or more of insulin or glucagon.
  • the variation in the monitored analyte level in still another aspect may be associated with a carbohydrate intake event.
  • the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to transmit the modified medication delivery rate frequency to a medication delivery unit, where the medication delivery unit may include an insulin pump.
  • the modified medication delivery rate frequency may be transmitted wirelessly to the medication delivery unit.
  • the device in yet still a further aspect may include a strip port to receive a blood glucose test strip including a blood sample, where the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to determine a blood glucose value based on the blood sample.

Abstract

Methods, system and devices for monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determining a variation in the monitored analyte level, determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjusting the closed loop control operation to modify the medication delivery rate frequency are provided.

Description

VARIABLE RATE CLOSED LOOP CONTROL AND METHODS
PRIORITY
The present applications claims priority to U.S. Patent Application No. 12/202,306 filed August 31 , 2008, entitled "Variable Rate Closed Loop Control and
Methods", the disclosure of which is incorporated herein by reference for all purposes.
BACKGROUND Benefits of a closed loop control system for treating diabetic conditions with monitoring glucose levels and adjusting delivery rate of insulin are well known. Such systems, referred to as artificial pancreas, model healthy pancreas which, when functioning normally, produces insulin (by the beta cells (β-cells)) to counteract the rise in glucose levels in the blood stream. As is known, Type-1 diabetes mellitus condition exists when the beta cells in the pancreas either die or are unable to produce sufficient amount of insulin naturally in response to the elevated glucose levels.
Common treatment of Type-1 diabetes is the use of insulin pumps that are programmed to continuously deliver insulin to the body through an infusion set. The use of insulin pumps to treat Type-2 diabetes (where the beta cells in the pancreas do produce insulin, but an inadequate quantity) is also becoming more prevalent. Such insulin delivery devices are preprogrammed with delivery rates such as basal profiles which are tailored to each user, and configured to provide the needed insulin to the user. Additionally, the preprogrammed delivery rates may be supplemented with periodic administration of bolus dosages of insulin (for example, correction bolus or carbohydrate bolus) as may be needed by the user.
In addition, continuous glucose monitoring systems have been developed to allow real time monitoring of fluctuation in glucose levels. One example is the FreeStyle Navigator® Continuous Glucose Monitoring System available from Abbott Diabetes Care Inc., of Alameda, California. The use of such glucose monitoring systems provides the user with real time glucose level information. Using the continuous glucose monitoring system, for example, diabetics are able to determine when insulin is needed to lower glucose levels or when additional glucose is needed to raise the level of glucose. With the continued rise in the number of diagnosed diabetic conditions, there is on-going research to develop closed loop control systems to automate the insulin delivery based on the real time monitoring of the fluctuation in the glucose levels. Closed loop control algorithms such as, for example, proportional, plus integral, plus derivative (PID) control algorithm or model predictive control algorithm exist and are used to control the automatic delivery of insulin based on the glucose levels monitored. One key concern in such automated systems is safety. For example, the glucose sensor in the closed loop control system may enter failure mode (permanently or temporarily) in which case the monitored glucose level in the closed loop control system will introduce error and potentially result in undesirable or dangerous amount of insulin being administered. Additionally, the infusion component in the closed loop control system may have errors or experience failure modes that results in an inaccurate amount of insulin delivered to the user.
Indeed, safety considerations as well as accuracy considerations to address and/or minimize the potential unreliability in the components of the closed loop control system are important to provide a robust control system in the treatment of diabetic conditions.
SUMMARY In one aspect, there are provided a method and device for monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determining a variation in the monitored analyte level, determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjusting the closed loop control operation to modify the medication delivery rate frequency.
Also provided are systems and kits.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram illustrating an overall closed loop control system in accordance with one embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure; FIG. 3 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure;
FIG. 4 is a flowchart illustrating condition deviation monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure;
FIG. 5 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure; FIG. 6 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure;
FIG. 7 is a flowchart illustrating variable rate control in a closed loop control system in accordance with one embodiment of the present disclosure; FIG. 8 is a flowchart illustrating variable rate control in a closed loop control system in accordance with another embodiment of the present disclosure;
FIGS. 9-10 are flowcharts illustrating blood glucose measurement to improve accuracy of the closed loop control system in accordance with another embodiment of the present disclosure; FIG. 11 is a flowchart illustrating medication delivery information to determine analyte sensor condition in a closed loop control system in accordance with one embodiment of the present disclosure; and
FIG. 12 is a flowchart illustrating detection of false hypoglycemic alarm condition in a closed loop control system in accordance with one embodiment of the present disclosure.
DETAILED DESCRIPTION
Before embodiments of the present disclosure are described, 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 is 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 system for a robust closed loop control system with safety parameters for continuously monitoring at least one analyte such as glucose in body fluid and delivering suitable level of medication such as insulin. In certain embodiments, the present disclosure relates to the continuous and/or automatic in vivo monitoring of the level of an analyte using an analyte sensor, and under the control of a closed loop control algorithm, determining and delivering an appropriate level of medication such as insulin in response to the monitored analyte level.
Embodiments includes medication delivery devices such as external infusion pumps, implantable infusion pumps, on-body patch pump, or any other processor controlled medication delivery devices that are in communication with one or more control units which also control the operation of the analyte monitoring devices. The medication delivery devices may include one or more reservoirs or containers to hold the medication for delivery in fluid connection with an infusion set, for example, including an infusion tubing and/or cannula. The cannula may be positioned so that the medication is delivered to the user or patient at a desired location, such as, for example, in the subcutaneous tissue under the skin layer of the user.
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. A sensor (and/or a sensor insertion apparatus) may be, for example, configured to be positionable in a patient for the continuous or periodic monitoring of a level of an analyte in a patient's dermal fluid. For the purposes of this description, continuous monitoring and periodic monitoring will be used interchangeably, unless noted otherwise. The analyte level may be correlated and/or converted to analyte levels in blood or other fluids. In certain embodiments, an analyte sensor may be configured to be positioned in contact with dermal fluid to detect the level of glucose, which detected glucose may be used to infer the glucose level in the patient's bloodstream. For example, analyte sensors may be insertable through the skin layer and into the dermal layer under the skin surface at a depth of approximately 3 mm under the skin surface and containing dermal 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, months, 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, the rate of change of the analyte, etc. Predictive alarms may notify the control unit (and/or the user) of predicted analyte levels that may be of concern in advance of the analyte level reaching the future level. This enables the control unit to determine a priori a suitable corrective action and implement such corrective action.
FIG. 1 is a block diagram illustrating an overall closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIG. 1, in one aspect, the closed loop control system 100 includes an insulin delivery unit 120 that is connected to a body 110 of a user or patient to establish a fluid path to deliver medication such as insulin. In one aspect, the insulin delivery unit 120 may include an infusion tubing fluidly connecting the reservoir of the delivery unit 120 to the body 110 using a cannula with a portion thereof positioned in the subcutaneous tissue of the body 110.
Referring to FIG. 1, the system 100 also includes an analyte monitoring device 130 that is configured to monitor the analyte level in the body 110. As shown in FIG.
1, a control unit 140 is provided to control the operation of the insulin delivery unit 120 and the analyte monitoring unit 130. In one embodiment, the control unit 140 may be a processor based control unit having provided therein one or more closed loop control algorithm to control the operation of the analyte monitoring device 130 and the delivery unit 120. In one aspect, the control unit 140, the analyte monitoring unit 130 and the delivery unit 120 may be integrated in a single housing. In other embodiments, the control unit 140 may be provided in the housing of the delivery unit 120 and configured for communication (wireless or wired) with the analyte monitoring unit 130. In an alternate embodiment, the control unit may be integrated in the housing of the analyte monitoring unit 130 and configured for communication (wireless or wired) with the delivery unit 120. In yet another embodiment, the control unit 140 may be a separate component of the overall system 100 and configured for communication (wireless or wired) with both the delivery unit 120 and the analyte monitoring unit 130.
Referring back to FIG. 1, the analyte monitoring unit 130 may include an analyte sensor that is transcutaneously positioned through a skin layer of the body 110, and in signal communication with a compact data transmitter provided on the skin layer of the body 110 which is configured to transmit the monitored analyte level substantially in real time to the analyte monitoring unit 130 for processing and/or display. In another aspect, the analyte sensor may be wholly implantable in the body 110 with a data transmitter and configured to wirelessly transmit the monitored analyte level to the analyte monitoring unit 130. Referring still to FIG. 1, also shown in the overall system 100 is a data processing device 150 in signal communication with the one or more of the control unit 140, delivery unit 120 and the analyte monitoring unit 130. In one aspect, the data processing device 150 may include an optional or supplemental device in the closed loop control system to provide user input/output functions, data storage and processing. Examples of the data processing device 150 include, but not limited to mobile telephones, personal digital assistants (PDAs), in vitro blood glucose meters, Blackberry® devices, iPhones, Palm® devices, data paging devices, and the like each of which include an output unit such as one or more of a display, audible and/or vibratory output, and/or an input unit such as a keypad, keyboard, input buttons and the like, and which are configured for communication (wired or wireless) to receive and/or transmit data, and further, which include memory devices such as random access memory, read only memory, volatile and/or non- volatile memory that store data.
Also shown in the overall system 100 is a data processing terminal 160 which may include a personal computer, a server terminal, a laptop computer a handheld computing device, or other similar computing devices that are configured to data communication (over the internet, local area network (LAN), cellular network and the like) with the one or more of the control unit 140, the delivery unit 120, the analyte monitoring unit 130, or the data processing device 150, to process, analyze, store, archive, and update information.
It is to be understood that the analyte monitoring device 130 of FIG. 1 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, DNA, fructosamine, glucose, glutamine, growth hormones, hormones, ketones, 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.
Additional detailed descriptions of embodiments of the continuous analyte monitoring device and system, calibrations protocols, embodiments of its various components are provided in U.S. Patent Nos. 6,175,752; 6,284,478; 7,299,082; US patent application No. 10/745,878 filed December 26, 2003 entitled "Continuous Glucose Monitoring System and Methods of Use", each incorporated by reference in its entirety for all purposes. Additional detailed description of systems including medication delivery units and analyte monitoring devices, embodiments of the various components are provided in US application patent application no. 11/386,915, entitled "Method and System for Providing Integrated Medication Infusion and Analyte Monitoring System" disclosure of which are incorporated by reference for all purposes. Moreover, additional detailed description of medication delivery devices and its components are provided in U.S. Patent No. 6,916,159, the disclosure of which is incorporated by reference for all purposes.
Referring back to FIG. 1, each of the components shown in the system 100 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, for example, by exchanging or pre-storing and/or verifying unique device identifiers as part of communication between the devices, by using periodic keep alive signals, or configuration of one or more devices or units in the overall system as a master-slave arrangement with periodic bi-directional communication to confirm integrity of signal communication therebetween.
Further, data communication may be encrypted or encoded (and subsequently decoded by the device or unit receiving the data), or transmitted using public-private keys, to ensure integrity of data exchange. Also, error detection and/or correction using, for example, cyclic redundancy check (CRC) or techniques may be used to detect and/or correct for errors in signals received and/or transmitted between the devices or units in the system 100. In certain aspects, data communication may be responsive to a command or data request received from another device in the system 100, while some aspects of the overall system 100 may be configured to periodically transmit data without prompting (such as the data transmitter, for example, in the analyte monitoring unit 130 periodically transmitting analyte related signals.
In certain embodiments, the communication between the devices or units in the system 100 may include one or more of an RF communication protocol, an infrared communication protocol, a Bluetooth enabled communication protocol, an
802.1 Ix wireless communication protocol, internet connection over a data network 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. In certain embodiments, data processing device 150, analyte monitoring unit
130 and/or delivery unit 120 may include blood glucose meter functions or capability to receive blood glucose measurements. For example, the housing of these devices may include a strip port to receive a blood glucose test strip with blood sample to determine the blood glucose level. Alternatively, a user input device such as an input button or keypad may be provided to manually enter such information. Still further, upon completion of a blood glucose measurement, the result may be wirelessly and/or automatically transmitted to another device in the system 100. For example, it is desirable to maintain a certain level of water tight seal on the housing of the delivery unit 120 during continuous use by the patient or user. In such case, incorporating a strip port to receive a blood glucose test strip may be undesirable. As such, the blood glucose meter function including the strip port may be integrated in the housing of another one of the devices or units in the system (such as in the analyte monitoring unit 103 and/or data processing device 150). In this case, the result from the blood glucose test, upon completion may be wirelessly transmitted to the delivery unit 120 for storage and further processing.
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® or Precision® 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 the analyte sensor, confirm results of the sensor to increase the confidence in the accuracy level thereof (e.g., in instances in which information obtained by sensor is employed in therapy related decisions), determine suitable amount of bolus dosage for administration by the delivery unit 120.
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 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.
One or more devices or components of the system 100 may include an alarm system that, e.g., based on information from control unit 140, 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 reaches or exceeds a threshold rate of change or acceleration. For example, in the case of the glucose monitoring unit 130, 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. In the case of the delivery unit 120, alarms may be associated with occlusion conditions, low reservoir conditions, malfunction or anomaly in the fluid delivery and the like. System alarms may also 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. Referring yet again to FIG. 1, the control unit 140 of the closed loop control system 100 may include one or more processors such as microprocessors and/or application specific integrated circuits (ASIC), volatile and/or non-volatile memory devices, and additional components that are configured to store and execute one or more closed loop control algorithms to dynamically control the operation of the delivery unit 120 and the analyte monitoring unit 130. The one or more closed loop control algorithms may be stored as a set of instructions in the one or more memory devices and executed by the one or more processors to vary the insulin delivery level based on, for example, glucose level information received from the analyte sensor.
As discussed in further detail below, the one or more control algorithms of the control unit 140 are configured to monitor parameters and conditions associated with a safety indication of the closed loop control system 100 and generate and notify the user, as may be desirable to perform one or more troubleshooting actions and/or automatically revert to a semi-closed loop control mode or a manual control mode that require some level of user, patient or healthcare provider intervention.
FIG. 2 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 2, in one embodiment, control unit 140 executing the closed loop system control is configured to monitor the closed loop control operation parameters (210). In one aspect, the closed loop control operation parameters may be associated with the operation of the delivery unit 120, and operational conditions associated therewith such as fluid delivery, amount of insulin delivered, potential occlusion and the like. In addition the closed loop control operation parameters monitored may also include operational conditions associated with the analyte monitoring unit 130 such as, for example, the validity or integrity of analyte sensor signals, unanticipated sensor signal drop out, missing sensor data, and the like. Further, in embodiments where the delivery unit 120 and analyte monitoring unit 130 are separate components in the system 100 communicating via wireless connection, monitored control operation parameters may include the integrity of the communication connection between the devices or units in the system 100.
Referring to FIG. 2, when based on the monitored closed loop operation parameters an adverse condition associated with a safety state of the closed loop operation is detected (220), it is determined whether the detected adverse condition exceeds a preset safety level (230). For example, in the case where the adverse condition is associated with the integrity of analyte sensor signals, it is determined whether sufficiently accurate glucose level can be derived based on the received sensor signals (for example, based on extrapolation using previously received sensor data, and/or in conjunction with a rate of change of glucose level determination). The adverse condition detected may also include a determined medication delivery level that exceeds a preset threshold level (for example, a physician determined maximum basal delivery rate for the user). As a further example, the adverse condition detected may include communication failure between the components of the overall system
100 including, the analyte monitoring unit 130 and the delivery unit 120.
Referring back to FIG. 2, when it is determined that the detected adverse condition does not exceed a preset safety level, in one aspect, the control unit 140 is configured to proceed with the execution of the closed loop control algorithm to based on the real time glucose data received from the analyte monitoring unit 130 to adjust the insulin delivery rate from the delivery unit 120, and the routine returns to monitoring the closed loop operation parameters. On the other hand, if it is determined that the detected adverse condition exceeds the preset safety level, the control unit 140 in one embodiment is configured to command or instruct the delivery unit 120 to revert to a non-zero pre-programmed closed loop operation state within the safety level (240). For example, when it is determined that the determined insulin level for delivery exceeds the safety level or maximum delivery rate (for example, established by a physician or healthcare provider, or the user, and programmed and stored in the control unit 140), the control unit 140 is configured to automatically revert to an insulin delivery rate that is within the safety level so that potential overdosing may be avoided.
In another aspect, the control unit 140 may be configured to issue a command to the delivery unit 120 every 15 minutes (or some other predetermined time interval) which sets insulin delivery rate for a 20 minute time period (or some other suitable time period). In the event that the adverse condition exceeding the preset safety level is detected preventing the control unit 140 to issue a new command to the delivery unit 120 during the 20 minute time period, the control unit 140 is configured to instruct the delivery unit 120 to revert to a pre-programmed delivery rate that is within the safety level (for example, a less amount of insulin to be delivered). In a further aspect, the detected adverse condition may include a determination of insulin on board value that, in conjunction with the insulin amount to be delivered exceeds the upper safely level of insulin delivery, the control unit 140 may be configured to revert to or switch to a preset or pre-programmed level that would bring the insulin delivery amount to be within the determined safety level.
As discussed, in one aspect, the insulin delivery amount that is within the safety level may be pre-programmed in the control unit 140, for example, and implemented as part of the closed loop control to automatically deliver the insulin amount based on the pre-programmed level. In a further aspect, the control unit 140 may be configured to modify or adjust the existing insulin delivery rate that is within the safety level in response to the detected adverse condition, (for example, reducing the determined insulin delivery rate by a certain factor such as 75%, to maintain the insulin delivery amount within the safety level). In this manner, in one aspect, when adverse condition associated with the safety state of the closed loop control operation, the control unit 140 may be configured to operate within a predefined safety range rather than requesting user intervention or disabling the closed loop control operation to revert to a manual control operation mode. While certain examples of adverse conditions are discussed above, within the scope of the present disclosure, any other condition associated with the safety level in the operation of the closed loop control system 100 are contemplated, the detection of any of which initiates the evaluation of the detected condition and appropriate modification to the closed loop control system parameters to continue operation of the closed loop control operation without prematurely disabling the system, while maintaining the desired level of safety in using the closed loop control system 100.
FIG. 3 is a flowchart illustrating adverse condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure. Referring to FIGS. 1 and 3, in one embodiment, control unit 140 (FIG. 1) retrieves a preset safety level information (310) and compares the retrieved preset safety level information to one or more detected adverse condition (320). Thereafter, a level of severity associated with the detected adverse condition is determined based, at least in part on the retrieved preset safety level information (330). After determining the severity level, the control unit 140 is configured to generate one or more closed loop operation instructions based on the determined severity level for execution.
That is, in one aspect, when an adverse condition is detected by the control unit 140, the control unit 140 (FIG. 1) is configured in one aspect to determine how severe is the detected adverse condition with respect to the automated insulin delivery. For example, control unit 140 may detect a communication failure from the transmitter of the analyte monitoring unit 130 and thus not receive a current sensor data indicative of the glucose level. However, the control unit 140 may have stored in one or more of its memory units previously received glucose levels from the transmitter of the analyte monitoring unit 130. Given an insulin delivery rate that is within the safety level, and a relatively stable glucose value (for example, based on a rate of change of glucose determination from previously received glucose data), the control unit 140 may be configured to declare the communication failure as a non- critical adverse condition detected. In this manner, the generated closed loop operation instruction (340) may not modify the current delivery rate by the delivery unit 120 (FIG. 1).
On the other hand, if the rate of change of the glucose level indicated by previously received sensor data demonstrates a rapid variation in the glucose level, and/or the communication failure persists over a time period that exceeds a certain level (for example, exceeding 20 minutes or some other suitable time frame), the generated closed loop operation instruction (340) may include commands to the delivery unit 120 (FIG. 1) to modify the delivery rate and/or revert to a preprogrammed delivery rate that are within the previously determined safety level. In one aspect, the control unit 140 (FIG. 1) may be configured to continuously monitor the presence of the detected adverse condition until the condition is corrected, in which case, the generated closed loop operation instruction (340) may include commands to the delivery unit 120 to return to the prior closed loop control operation. FIG. 4 is a flowchart illustrating condition deviation monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 4, in another aspect, control unit 140 (FIG. 1) monitors the closed loop operation parameters (410) and when it detects one or more monitored closed loop operation parameters deviating from a predetermined level
(420), the control unit 140 (FIG. 1) may be configured to generate and output a request for confirmation of the detected deviation of the monitored closed loop operation parameter (430).
For example, in the closed loop control system 100 (FIG. 1), a user interface such as a display unit or audible/vibratory notification in the insulin delivery unit 120 and/or the analyte monitoring unit 130 may indicate a notification for the user to confirm the presence of the detected deviation of the monitored closed loop operation parameter. Referring to FIG. 4, if the detected deviation of the monitored closed loop operation parameter is confirmed (440), in one aspect, the control unit 140 (FIG. 1) may be configured to modify the closed loop control operation based on the detected deviation of one or more of its parameters (450). On the other hand, if the presence of the detected deviation of the monitored closed loop operation parameter is not confirmed, then the control unit 140 (FIG. 1) may be configured to disable the closed loop control operation, and initiate a manual operation mode (460) to deliver insulin by the delivery unit 120 (FIG. 1).
In this manner, in one aspect, the control unit 140 (FIG. 1) may be configured to request for user confirmation or verification of the presence of the detected adverse condition prior to initiating responsive corrective action, and further, when no verification or confirmation is received, for example, within a set time period, the control unit 140 (FIG. 1) may be configured to disable the closed loop control operation. Accordingly, certain adverse conditions detected may prompt the control unit 140 (FIG. 1) to request confirmation prior to automatically responding to such occurrence of adverse condition, and further, when no confirmation is received, the control unit 140 (FIG. 1) may temporarily revert to a semi-closed loop or non-closed loop manual delivery mode. In this manner, in certain aspects, a level of safety in using the closed loop control system 100 is maintained, and depending upon the particular detected adverse condition, the control unit 140 may automatically, temporarily adjust the delivery mode of the delivery unit 120 (FIG. 1), or alternatively, require user intervention.
Furthermore, within the scope of the present disclosure, while the detected conditions are described as adverse conditions, any parameter or condition associated with the operation of the closed loop control system 100 are contemplated including but not limited to, analyte sensor operation, sensor signal filtering, sensor signal level, sensor calibration, sensor signal attenuation, communication failure, signal outlier condition, rate of change of the glucose level, insulin delivery rate, insulin on board information, type of insulin, duration of the closed loop control operation, number or frequency of bolus dosage administration, predicted or projected glucose level and/or the direction of the predicted or projected glucose level, frequency of blood glucose measurements, maximum or minimum insulin delivery level, for example.
FIG. 5 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 5, in one embodiment, control unit 140
(FIG. 1) is configured to monitor closed loop operation parameters (510) in the closed loop control system 100 (FIG. 1). When a potential fault or failure mode associated with the operation of the analyte sensor is detected (520), the control unit 140 is configured to retrieve and execute a preprogrammed delivery rate (530) (for example, a predetermined basal profile), while maintaining the closed loop control operation mode. Further, the control unit 140 is configured to generate and output instructions or request to confirm and/or correct the detected potential fault or failure mode of the analyte sensor (540).
That is, in one aspect, the closed loop control operation is not disabled when it is initially detected that the analyte sensor may not be properly functioning. Rather, the closed loop control operation includes the execution of a pre-programmed delivery rate that is determined to be within a safety level, and when the potential fault condition or failure mode has been corrected, the control unit 140 may be configured to terminate the execution of the pre-programmed delivery rate and resume real time automatic adjustment to the insulin delivery rate based on the analyte sensor signals.
In this manner, rather than prematurely terminating the operation of the closed loop control system 100 at a first indication of potential failure or fault of the analyte sensor, in one aspect, the control unit 140 is configured to instruct the delivery unit 120 to execute a predetermined delivery rate that is within the safety level until corrective action related to the analyte sensor (for example, replacing the sensor, or recalibrating the sensor with a blood glucose measurement) is performed. In a further aspect, the control unit 140 may be configured to modify the retrieved predetermined delivery rate based on the insulin delivered (for example, to consider the insulin on board level) so that the safety level associated with the amount of insulin to be delivered is maintained.
FIG. 6 is a flowchart illustrating analyte sensor condition monitoring and control in a closed loop control system in accordance with another embodiment of the present disclosure. Referring to FIGS. 1 and 6, in another aspect, when the control unit 140 receives analyte sensor operation information (610), one or more routines are performed to confirm the proper operation of the analyte sensor (620). For example, the control unit 140 may be configured to verify the calibration information of the analyte sensor so that the value level derived therefrom accurately indicates the monitored glucose level.
In a further aspect, the control unit 140 may be configured to retrieve the most recent sensor sensitivity determination based, for example, on the reference blood glucose measurement received, and to compare the retrieved sensitivity to a stored nominal sensitivity for the sensor to confirm a variation between sensitivities not exceeding a predetermined level. In another aspect, when a scheduled calibration event occurs to calibrate the analyte sensor, the current blood glucose measurement is used to determine an updated sensor sensitivity value which may be used in conjunction with one or more prior sensitivity values or nominal sensitivity value. Referring back to FIG. 6, when it is confirmed that the analyte sensor is in proper operation mode, the preprogrammed delivery rate executed by the delivery unit 120 (FIG. 1) initiated when the sensor potential failure mode was detected, is terminated (630), and the closed loop control operation based on the analyte sensor signals is re-initiated (640). In the manner described above, in accordance with embodiments of the present disclosure, the operation of the closed loop control system 100 may include monitoring the condition or parameters associated with the analyte monitoring unit 130 and for example, the analyte sensor, and execute one or more routines to instruct the delivery unit 120 to temporarily execute preprogrammed or modified delivery profile determined to be within the safety limits, or to disable the closed loop control operation to maintain the desired degree of safety in using the closed loop control system 100 (FIG. 1). Indeed, in one aspect, for example, when an analyte sensor reading erroneously indicates a high level of glucose which is a false positive value and where the actual glucose level is lower than the measured high level of glucose, aspects of the closed loop control operation are configured to establish a limit in the amount of insulin delivered so that when sensor failure is detected, delivery of insulin amount beyond the determined safe level is prevented. FIG. 7 is a flowchart illustrating variable rate control in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 7, in one aspect, control unit 140 executing the closed loop control algorithm in the closed loop control system 100 receives monitored analyte level at a predetermined frequency (710). Based at least in part of the received monitored analyte level, the analyte variation level is determined (720). Thereafter, as shown, the medication delivery rate adjustment frequency is determined based on the determined analyte variation level (730), and thereafter, the delivery unit 120 (FIG. 1) is instructed to deliver the medication at the determined medication delivery rate adjustment frequency (740). That is, in one aspect, the rate of monitored glucose level is associated with the adjustment of the frequency in which to instruct the delivery unit 120 to deliver insulin.
For example, in one aspect, the control unit 140 may be configured to monitor the glucose level from the analyte monitoring unit 130 at a higher frequency (such as, for example once per minute), and also, adjust the rate of insulin delivery by the delivery unit 120 (FIG. 1) at a lower frequency (for example, once every 15 minutes).
Indeed, it may be unnecessary to adjust the rate of insulin delivery more frequently than once every 15 minutes when the monitored glucose level (at a higher frequency) does not indicate significant variation in the glucose level. Accordingly, control unit 140 may be configured to issue an instruction or command to the delivery unit 120 once every 15 minutes (or some other suitable interval) to vary the delivery rate based on the glucose level.
One advantage resulting from the less frequent delivery rate adjustment is the conservation of power in the control unit 140 and/or the delivery unit 120. That is, battery power may be conserved by avoiding the generation, communication and/or execution of instructions or commands associated with determining and implementing modification to the insulin delivery rate. On the other hand, since the glucose level is monitored every minute (or at a more frequent time interval), control unit 140 is configured to monitor the variation in the glucose level monitored, and as long as the variation is within a threshold level, the corresponding insulin level delivery adjustment determination is not executed with the same or similar frequency.
However, when the variation in the monitored glucose level exceeds the predetermined threshold level indicating a large variation in the monitored glucose level, or in the cases where a meal event or carbohydrate intake event occurs which will impact the monitored glucose level, it may be desirable to adjust the rate of insulin delivery to be more frequent (for example, adjustment to the delivery rate once every 5 minutes rather than 15 minutes, or with each determination of the glucose level). In this manner, to the extent that adjustment to the insulin delivery rate is desirable, the frequency of the adjustment may be associated with the monitored glucose level such that, for example, control unit 140 may be configured to determine, with each received glucose value, whether adjustment to the insulin delivery rate is needed.
FIG. 8 is a flowchart illustrating variable rate control in a closed loop control system in accordance with another embodiment of the present disclosure. Referring to FIGS. 1 and 8, control unit 140 (FIG. 1) in one aspect may be configured to instruct the delivery unit 120 (FIG. 1) to deliver medication based on closed loop control parameters at a first delivery rate adjustment frequency (810). Thereafter, the analyte variation level is determined based on the monitored analyte level at a predetermined frequency (820). Referring back to FIG. 8, one or more condition information (for example, but not limited to an anticipated meal event) associated with the closed loop control parameters is received (830). Thereafter, a second delivery rate adjustment frequency is determined based on the analyte level variation and/or received condition information (840), and the medication delivery is executed (for example, by the insulin delivery unit 120 (FIG. I)) at the determined second delivery rate adjustment frequency (850).
In this manner, in one aspect, control unit 140 is configured to maximize responsiveness to substantial variation in monitored glucose level, or in anticipation of variation in glucose level, while providing lower power requirements for the various components of the system 100 (FIG. 1). Within the scope of the present disclosure, other suitable time intervals or frequency may be used for the glucose monitoring, and further, the associated adjustment to the insulin delivery rate. That is, embodiments of the present disclosure allow for lower rate of control commands, for example, where the delivery unit 120 and the analyte monitoring unit 130 are configured in the system 100 as separate components, with the control unit 140 provided with the analyte monitoring unit 130 and communicating wirelessly with the delivery unit 120, and each being powered by a respective power supply such as a battery.
FIGS. 9-10 are flowcharts illustrating blood glucose measurement to improve accuracy of the closed loop control system in accordance with another embodiment of the present disclosure. Referring to FIGS. 1, 9 and 10, closed loop operation parameters are monitored (910) and when onset of medication delivery level (for example, a large insulin dosage level) that exceeds a predetermined threshold level is detected (920) a blood glucose measurement information is received (930) (for example, from a blood glucose meter or manually entered by user input). Based on the received blood glucose measurement information, it is determined whether the received blood glucose measurement is within a predetermined margin of error to a time corresponding analyte sensor data (940). In other words, it is determined whether the sensor data correlates to the blood glucose measurement within a predetermined margin of error.
Referring back to FIG. 9, if it is determined that the analyte sensor data and the blood glucose measurement are within the predetermined margin of error, then the detected onset of medication delivery level is maintained and the delivery unit 120 delivers that level of medication (950). On the other hand, if it is determined that the blood glucose measurement received is not within the predetermined margin of error (940), then referring back to FIG. 10 (960), the closed loop control parameters associated with the analyte monitoring and/or the medication delivery are retrieved (1010), and the retrieved closed loop control parameters are evaluated based on the received blood glucose measurement (1020).
For example, one or more of the closed loop control parameters retrieved may include a request for an additional blood glucose measurement value, an instruction to modify or adjust insulin delivery rate, command to disable closed loop control operation and initiate semi-closed loop control operation or manual control operation, or instruction to recalibrate the analyte sensor, among others. Referring back to FIG. 10, upon evaluation of the retrieved one or more closed loop control parameters, the retrieved one or more parameters may be modified (1030) and thereafter the modified one or more closed loop control parameters is stored (1040).
In this manner, for example, under the control of the control unit 140 (FIG. 1) executing the closed loop control algorithm, when it is detected that a large amount of insulin is to be delivered by the delivery unit 120, the control unit 140, as a safety measure, for example, may prompt the user to enter a current blood glucose measurement (for example, using an in vitro blood glucose meter), to confirm and/or verify the accuracy of the analyte sensor level from the analyte monitoring unit 130 based on which the large amount of insulin to be delivered was determined for execution. For example, a Kalman filter may be used as part of the control unit 140 to process the analyte sensor data and the received blood glucose measurement to optimally adjust the insulin level.
In one aspect, the request or prompt to enter the blood glucose measurement may be initiated when the determined insulin amount for delivery in the closed loop control system 100 exceeds a predetermined safety level established, for example, by a healthcare provider or physician, where the safety level includes, for example, the highest insulin delivery rate without blood glucose measurement confirmation. Within the scope of the present disclosure, other conditions or parameters may be used to trigger the request for blood glucose measurement for confirming sensor accuracy, glucose level verification, and the like. Further, in another aspect, the control unit 140 may be configured to discontinue requesting blood glucose measurements (even when the insulin level to be delivered exceeds the predetermined safety level) when a predetermined number of successful blood glucose measurement confirmations have occurred and the analyte sensor is considered accurate and stable. Still another aspect of the present disclosure includes modifying the safety level for the highest rate of insulin delivery based on the determination of sensor stability and accuracy in view of, for example, successive confirmation of blood glucose measurements to the corresponding sensor values. FIG. 11 is a flowchart illustrating medication delivery information to determine analyte sensor condition in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 11, in the closed loop control operation state of the closed loop control system 100, control unit 140 (FIG. 1) in one aspect monitors closed loop operation parameters (1110) and performs a predictive modeling analysis of the monitored closed loop control operation parameters associated with the medication delivery and analyte sensor to determine a predictive glucose response (1120). Thereafter, the determined predictive glucose response is compared with the corresponding monitored analyte sensor signal (1130) and a sensor signal condition based on the comparison is determined (1140). For example, based on the comparison, the sensor signal condition may indicate a signal attenuation condition of the glucose sensor. Referring back to FIG. 11, when the sensor signal condition indicates an adverse signal condition or a condition associated with a corrective action or procedure, the corresponding corrective procedure is retrieved and executed by the control unit 140 (1150).
In this manner, in one aspect, using the insulin delivery information, and based on a predictive model implemented to determine a modeled glucose sensor signal, the robustness of the closed loop control system 100 may be enhanced and accuracy of the overall system 100 improved. In one aspect, the predictive model used may include a routine or algorithm that describes glucose response or behavior based on one or more exogenous factors including, among others, insulin delivery information, meal intake, exercise events, and the like, as well as prior monitored sensor data. Accordingly, in one aspect, real time insulin delivery information may be used to improve glucose sensor anomalies such as signal dropouts and early signal attenuation.
For example, as discussed above, the generated modeled glucose sensor response is compared in one aspect to the actual measured sensor data, and based on the comparison, it may be determined that anomalies exist with the glucose sensor. For example, control unit 140 may determine, based on the comparison that sensor signal dropout or early signal attenuation is detected, and thus may prompt the user to enter a reference blood glucose measurement value. In addition, certain alarm or notification functions related to the monitored analyte level such as hypoglycemic alarm, output display of glucose values in real time, may be modified or disabled given the detected anomaly with the sensor signal.
In one aspect, other variables may be compared based on the predictive model and the actual measured sensor signal such as, for example, rate of change of the glucose level determined based on the actual measured values from the sensor and compared with the modeled rate of change information. Additionally, upon determination of the sensor signal drop out or early signal attenuation condition, operations of the analyte monitoring unit 130 may be adjusted accordingly, for example, to mitigate or address the signal abnormality. For example, when such sensor signal condition indicates adverse signal condition at the time of scheduled sensor calibration, the calibration attempt may be disqualified and the user may be instructed to perform another calibration or to delay the calibration until the sensor signal has stabilized and the indicated adverse signal condition is no longer present. FIG. 12 is a flowchart illustrating detection of false hypoglycemic alarm condition in a closed loop control system in accordance with one embodiment of the present disclosure. Referring to FIGS. 1 and 12, in one aspect, condition associated with hypoglycemic state is detected (1220) based on monitored closed loop operation parameters (1210) by, for example, the control unit 140 (FIG. 1). Upon detection of the condition associated with the hypoglycemic state, a pre-hypoglycemic condition notification routine is performed (1230). If the hypoglycemic state or condition is confirmed (1240), then a corresponding notification such as a hypoglycemic alarm is output (1250), and the closed loop control parameters are accordingly updated to take into account of the detected hypoglycemic condition (1260).
On the other hand, if the hypoglycemic condition is not confirmed (1240), then the routine returns to monitor the closed loop operation parameters (1210). That is, in one aspect, when a condition associated with hypoglycemia is detected, the control unit 140 may be configured to confirm the presence of the detected hypoglycemic state before asserting an alarm notification, for example, to the user. In this manner, potential false hypoglycemic alarms are minimized based on, for example, presence of glucose sensor signal dropout or early signal attenuation or other sensor anomaly state that indicates a false low glucose level.
For example, in accordance with the embodiments of the present disclosure, hypoglycemic alarms or notifications are provided with sensor signal dropout tolerance levels. More specifically, based on the medication delivery rate information, and other parameters associated with the closed loop control operation, the control unit 140 may be configured to determine a degree or level of uncertainly in the measured sensor signal based on the predicted or anticipated glucose level derived, for example, based on the parameters associated with the closed loop control algorithm, including, such as amount of insulin delivered, insulin on board information, glucose rate of change information, among others.
In one aspect, when the onset of a potential hypoglycemic condition is detected, the control unit 140 may be configured to confirm the presence of the hypoglycemic condition, by for example, requiring additional sensor data to be received and analyzed and determining that the sensor signals indicate a persistent low glucose value. In this manner, the rather than asserting the hypoglycemic condition notification immediately upon detection of a sensor signal level below the alarm threshold, control unit 140 in one aspect is configured to confirm the presence of the hypoglycemic condition, and upon confirmation, to assert the alarm or notification associated with the hypoglycemic condition.
In another aspect, upon detection of a potential hypoglycemic condition, control unit 140 may be configured to initiate and execute a sensor signal dropout detection algorithm to determine whether the detected potential hypoglycemic condition is associated with sensor signal dropout or attributable to low glucose level.
Moreover, in a further aspect, upon detection of the potential hypoglycemic condition, control unit 140 may be configured to assert an alert notification (associated with less urgency or criticality), and if the potential hypoglycemic condition is confirmed, to assert the hypoglycemic condition alarm. For example, the alert notification may include a single audible beep that does not repeat. If the glucose is persistently below the hypoglycemic threshold (or alarm condition level), or below a lower safety threshold, the notification may be escalated to an alarm, for example, with three consecutive audible beeps with or without repeat routines. In this manner, for example, if the sensor signal dropout occurs during night time when the user is asleep, the alert notification may not be loud enough to wake the user, but may be sufficient to cause the user to move or roll over in bed, for example, resulting in the sensor dropout condition being no longer present. In the manner described, in accordance with the various embodiments of the present disclosure, a robust closed loop control system is provided that includes safety checks and verifications to address potential errors and/or anomalies in detected or monitored conditions and/or parameters enhancing the accuracy and confidence level of the closed loop control operation in the treatment of diabetic conditions.
A method in accordance with one embodiment includes monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determining a variation in the monitored analyte level, determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjusting the closed loop control operation to modify the medication delivery rate frequency.
The predetermined frequency associated with the monitored signals the analyte sensor may be greater than the medication delivery rate frequency.
The analyte sensor in one embodiment includes a glucose sensor. The modification to the medication delivery rate frequency may be performed dynamically based in part on the determined variation in the monitored analyte level.
The closed loop control operation may be adjusted to modify the medication delivery rate frequency based on one or more of anticipated carbohydrate intake, anticipated exercise event, or anticipated change in the physiological condition. In another aspect, adjusting the closed loop control operation to modify the medication delivery rate frequency may be performed to minimize power consumption level associated with medication delivery.
The medication may include one or more of insulin or glucagon.
The variation in the monitored analyte level may be associated with a carbohydrate intake event.
A device in accordance with another embodiment includes one or more processors, and a memory operatively coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to monitor a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determine a variation in the monitored analyte level, determine a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjust the closed loop control operation to modify the medication delivery rate frequency.
In one aspect, the predetermined frequency associated with the monitored signals of the analyte sensor is greater than the medication delivery rate frequency. The analyte sensor in a further embodiment includes a glucose sensor.
The memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to dynamically perform the modification to the medication delivery rate frequency based in part on the determined variation in the monitored analyte level. The memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to adjust the closed loop control operation to modify the medication delivery rate frequency based on one or more of anticipated carbohydrate intake, anticipated exercise event, or anticipated change in the physiological condition. The memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to perform adjustment to the closed loop control operation to modify the medication delivery rate frequency to minimize power consumption level associated with medication delivery.
In one aspect, the medication may include one or more of insulin or glucagon. Also, the variation in the monitored analyte level in still another aspect may be associated with a carbohydrate intake event.
The memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to transmit the modified medication delivery rate frequency to a medication delivery unit, where the medication delivery unit may include an insulin pump.
In still another aspect, the modified medication delivery rate frequency may be transmitted wirelessly to the medication delivery unit.
The device in yet still a further aspect may include a strip port to receive a blood glucose test strip including a blood sample, where the memory for storing instructions which, when executed by the one or more processors, may cause the one or more processors to determine a blood glucose value based on the blood sample.

Claims

WHAT IS CLAIMED IS:
1. A method, comprising: monitoring a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency; determining a variation in the monitored analyte level; determining a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level; and adjusting the closed loop control operation to modify the medication delivery rate frequency.
2. The method of claim 1 wherein the predetermined frequency associated with the monitored signals the analyte sensor is greater than the medication delivery rate frequency.
3. The method of claim 1 wherein the analyte sensor includes a glucose sensor.
4. The method of claim 1 wherein the modification to the medication delivery rate frequency is performed dynamically based in part on the determined variation in the monitored analyte level.
5. The method of claim 1 wherein the closed loop control operation is adjusted to modify the medication delivery rate frequency based on one or more of anticipated carbohydrate intake, anticipated exercise event, or anticipated change in the physiological condition.
6. The method of claim 1 wherein adjusting the closed loop control operation to modify the medication delivery rate frequency is performed to minimize power consumption level associated with medication delivery.
7. The method of claim 1 wherein the medication includes one or more of insulin or glucagon.
8. The method of claim 1 wherein the variation in the monitored analyte level is associated with a carbohydrate intake event.
9. A device, comprising: one or more processors; and a memory operatively coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to monitor a closed loop control operation including signal levels received from an analyte sensor at a predetermined frequency, determine a variation in the monitored analyte level, determine a medication delivery rate adjustment frequency to deliver a medication based on the determined variation in the monitored analyte level, and adjust the closed loop control operation to modify the medication delivery rate frequency.
10. The device of claim 9 wherein the predetermined frequency associated with the monitored signals of the analyte sensor is greater than the medication delivery rate frequency.
11. The device of claim 9 wherein the analyte sensor includes a glucose sensor.
12. The device of claim 9 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to dynamically perform the modification to the medication delivery rate frequency based in part on the determined variation in the monitored analyte level.
13. The device of claim 9 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to adjust the closed loop control operation to modify the medication delivery rate frequency based on one or more of anticipated carbohydrate intake, anticipated exercise event, or anticipated change in the physiological condition.
14. The device of claim 9 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to perform adjustment to the closed loop control operation to modify the medication delivery rate frequency to minimize power consumption level associated with medication delivery.
15. The device of claim 9 wherein the medication includes one or more of insulin or glucagon.
16. The device of claim 9 wherein the variation in the monitored analyte level is associated with a carbohydrate intake event.
17. The device of claim 9 wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to transmit the modified medication delivery rate frequency to a medication delivery unit.
18. The device of claim 17 wherein the medication delivery unit includes an insulin pump.
19. The device of claim 17 wherein the modified medication delivery rate frequency is transmitted wirelessly to the medication delivery unit.
20. The device of claim 9 further including a strip port to receive a blood glucose test strip including a blood sample, wherein the memory for storing instructions which, when executed by the one or more processors, causes the one or more processors to determine a blood glucose value based on the blood sample.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3131464A4 (en) * 2014-04-15 2017-12-27 Insulet Corporation Monitoring a physiological parameter associated with tissue of a host to confirm delivery of medication
US11241532B2 (en) 2018-08-29 2022-02-08 Insulet Corporation Drug delivery system with sensor having optimized communication and infusion site

Families Citing this family (94)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8065161B2 (en) 2003-11-13 2011-11-22 Hospira, Inc. System for maintaining drug information and communicating with medication delivery devices
US9123077B2 (en) 2003-10-07 2015-09-01 Hospira, Inc. Medication management system
US9392969B2 (en) 2008-08-31 2016-07-19 Abbott Diabetes Care Inc. Closed loop control and signal attenuation detection
US8478557B2 (en) 2009-07-31 2013-07-02 Abbott Diabetes Care Inc. Method and apparatus for providing analyte monitoring system calibration accuracy
AU2007317669A1 (en) 2006-10-16 2008-05-15 Hospira, Inc. System and method for comparing and utilizing activity information and configuration information from mulitple device management systems
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
US20090143725A1 (en) * 2007-08-31 2009-06-04 Abbott Diabetes Care, Inc. Method of Optimizing Efficacy of Therapeutic Agent
US8409093B2 (en) 2007-10-23 2013-04-02 Abbott Diabetes Care Inc. Assessing measures of glycemic variability
US8377031B2 (en) 2007-10-23 2013-02-19 Abbott Diabetes Care Inc. Closed loop control system with safety parameters and methods
US8517990B2 (en) 2007-12-18 2013-08-27 Hospira, Inc. User interface improvements for medical devices
US20090164239A1 (en) 2007-12-19 2009-06-25 Abbott Diabetes Care, Inc. Dynamic Display Of Glucose Information
US7959598B2 (en) 2008-08-20 2011-06-14 Asante Solutions, Inc. Infusion pump systems 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
US8734422B2 (en) 2008-08-31 2014-05-27 Abbott Diabetes Care Inc. Closed loop control with improved alarm functions
CA2954728C (en) * 2008-09-15 2019-03-26 Deka Products Limited Partnership Systems and methods for fluid delivery
US8986208B2 (en) 2008-09-30 2015-03-24 Abbott Diabetes Care Inc. Analyte sensor sensitivity attenuation mitigation
US20120029942A1 (en) * 2009-04-17 2012-02-02 Arkray, Inc. User-Specific Data Provision System, User-Specific Data Provision Method, Server Device, and Handheld Device
US8271106B2 (en) 2009-04-17 2012-09-18 Hospira, Inc. System and method for configuring a rule set for medical event management and responses
EP2531232B1 (en) * 2010-02-05 2016-10-19 DEKA Products Limited Partnership Infusion pump apparatus and heated fill adapter system
US20110313680A1 (en) * 2010-06-22 2011-12-22 Doyle Iii Francis J Health Monitoring System
WO2012048168A2 (en) 2010-10-07 2012-04-12 Abbott Diabetes Care Inc. Analyte monitoring devices and methods
CA2844807C (en) 2011-08-19 2022-07-26 Hospira, Inc. Systems and methods for a graphical interface including a graphical representation of medical data
AU2012325937B2 (en) 2011-10-21 2018-03-01 Icu Medical, Inc. Medical device update system
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
US10022498B2 (en) * 2011-12-16 2018-07-17 Icu Medical, Inc. System for monitoring and delivering medication to a patient and method of using the same to minimize the risks associated with automated therapy
JP6306566B2 (en) 2012-03-30 2018-04-04 アイシーユー・メディカル・インコーポレーテッド Air detection system and method for detecting air in an infusion system pump
ES2743160T3 (en) 2012-07-31 2020-02-18 Icu Medical Inc Patient care system for critical medications
EP2890297B1 (en) 2012-08-30 2018-04-11 Abbott Diabetes Care, Inc. Dropout detection in continuous analyte monitoring data during data excursions
AU2014225658B2 (en) 2013-03-06 2018-05-31 Icu Medical, Inc. Medical device communication method
WO2014190264A1 (en) 2013-05-24 2014-11-27 Hospira, Inc. Multi-sensor infusion system for detecting air or an occlusion in the infusion system
ES2838450T3 (en) 2013-05-29 2021-07-02 Icu Medical Inc Infusion set that uses one or more sensors and additional information to make an air determination relative to the infusion set
AU2014274122A1 (en) 2013-05-29 2016-01-21 Icu Medical, Inc. Infusion system and method of use which prevents over-saturation of an analog-to-digital converter
US9561324B2 (en) 2013-07-19 2017-02-07 Bigfoot Biomedical, Inc. Infusion pump system and method
EP3039596A4 (en) 2013-08-30 2017-04-12 Hospira, Inc. System and method of monitoring and managing a remote infusion regimen
US9662436B2 (en) 2013-09-20 2017-05-30 Icu Medical, Inc. Fail-safe drug infusion therapy system
US10311972B2 (en) 2013-11-11 2019-06-04 Icu Medical, Inc. Medical device system performance index
EP3071253B1 (en) 2013-11-19 2019-05-22 ICU Medical, Inc. Infusion pump automation system and method
US10569015B2 (en) 2013-12-02 2020-02-25 Bigfoot Biomedical, Inc. Infusion pump system and method
GB2523989B (en) 2014-01-30 2020-07-29 Insulet Netherlands B V Therapeutic product delivery system and method of pairing
JP6636442B2 (en) 2014-02-28 2020-01-29 アイシーユー・メディカル・インコーポレーテッド Infusion systems and methods utilizing dual wavelength optical in-pipe air detection
US10722650B2 (en) 2014-03-28 2020-07-28 Roche Diabetes Care, Inc. System and method for adjusting therapy based on risk associated with a glucose state
US9764082B2 (en) 2014-04-30 2017-09-19 Icu Medical, Inc. Patient care system with conditional alarm forwarding
AU2015266706B2 (en) 2014-05-29 2020-01-30 Icu Medical, Inc. Infusion system and pump with configurable closed loop delivery rate catch-up
US9724470B2 (en) 2014-06-16 2017-08-08 Icu Medical, Inc. System for monitoring and delivering medication to a patient and method of using the same to minimize the risks associated with automated therapy
US9539383B2 (en) 2014-09-15 2017-01-10 Hospira, Inc. System and method that matches delayed infusion auto-programs with manually entered infusion programs and analyzes differences therein
US11344668B2 (en) 2014-12-19 2022-05-31 Icu Medical, Inc. Infusion system with concurrent TPN/insulin infusion
WO2016134137A1 (en) 2015-02-18 2016-08-25 Insulet Corporation Fluid delivery and infusion devices, and methods of use thereof
US10850024B2 (en) 2015-03-02 2020-12-01 Icu Medical, Inc. Infusion system, device, and method having advanced infusion features
US9878097B2 (en) 2015-04-29 2018-01-30 Bigfoot Biomedical, Inc. Operating an infusion pump system
CA2988094A1 (en) 2015-05-26 2016-12-01 Icu Medical, Inc. Infusion pump system and method with multiple drug library editor source capability
JP6986007B2 (en) 2015-07-10 2021-12-22 アボット ダイアベティス ケア インコーポレイテッドAbbott Diabetes Care Inc. Systems, devices and methods of dynamic glucose profile response to physiological parameters
DK3319511T3 (en) 2015-08-07 2021-11-01 Univ Boston Glucose management system with automatic adjustment of glucose targets
US10987468B2 (en) 2016-01-05 2021-04-27 Bigfoot Biomedical, Inc. Operating multi-modal medicine delivery systems
US10449294B1 (en) 2016-01-05 2019-10-22 Bigfoot Biomedical, Inc. Operating an infusion pump system
WO2017123525A1 (en) 2016-01-13 2017-07-20 Bigfoot Biomedical, Inc. User interface for diabetes management system
CA3009351A1 (en) 2016-01-14 2017-07-20 Bigfoot Biomedical, Inc. Adjusting insulin delivery rates
EP3454922B1 (en) 2016-05-13 2022-04-06 ICU Medical, Inc. Infusion pump system with common line auto flush
CA3027176A1 (en) 2016-06-10 2017-12-14 Icu Medical, Inc. Acoustic flow sensor for continuous medication flow measurements and feedback control of infusion
US20180003595A1 (en) * 2016-06-29 2018-01-04 Karl Veggerby Sealed water sampling device
NZ750032A (en) 2016-07-14 2020-05-29 Icu Medical Inc Multi-communication path selection and security system for a medical device
US10765807B2 (en) 2016-09-23 2020-09-08 Insulet Corporation Fluid delivery device with sensor
EP3600014A4 (en) 2017-03-21 2020-10-21 Abbott Diabetes Care Inc. Methods, devices and system for providing diabetic condition diagnosis and therapy
ES2903174T3 (en) 2017-05-05 2022-03-31 Lilly Co Eli Physiological glucose closed loop monitoring
CN111542884B (en) 2017-12-21 2024-03-15 益首药物治疗股份公司 Closed loop control of physiological glucose
US10089055B1 (en) 2017-12-27 2018-10-02 Icu Medical, Inc. Synchronized display of screen content on networked devices
USD928199S1 (en) 2018-04-02 2021-08-17 Bigfoot Biomedical, Inc. Medication delivery device with icons
CN112236826A (en) 2018-05-04 2021-01-15 英赛罗公司 Safety constraints for drug delivery systems based on control algorithms
US10950339B2 (en) 2018-07-17 2021-03-16 Icu Medical, Inc. Converting pump messages in new pump protocol to standardized dataset messages
US11139058B2 (en) 2018-07-17 2021-10-05 Icu Medical, Inc. Reducing file transfer between cloud environment and infusion pumps
EP3824386B1 (en) 2018-07-17 2024-02-21 ICU Medical, Inc. Updating infusion pump drug libraries and operational software in a networked environment
ES2962660T3 (en) 2018-07-17 2024-03-20 Icu Medical Inc Systems and methods to facilitate clinical messaging in a network environment
US10692595B2 (en) 2018-07-26 2020-06-23 Icu Medical, Inc. Drug library dynamic version management
WO2020023231A1 (en) 2018-07-26 2020-01-30 Icu Medical, Inc. Drug library management system
US11628251B2 (en) 2018-09-28 2023-04-18 Insulet Corporation Activity mode for artificial pancreas system
WO2020077223A1 (en) 2018-10-11 2020-04-16 Insulet Corporation Event detection for drug delivery system
JP2022541491A (en) 2019-07-16 2022-09-26 ベータ バイオニクス,インコーポレイテッド blood sugar control system
DE112020003406T5 (en) 2019-07-16 2022-06-23 Beta Bionics, Inc. BLOOD SUGAR CONTROL SYSTEM
US11801344B2 (en) 2019-09-13 2023-10-31 Insulet Corporation Blood glucose rate of change modulation of meal and correction insulin bolus quantity
US11935637B2 (en) 2019-09-27 2024-03-19 Insulet Corporation Onboarding and total daily insulin adaptivity
US11278671B2 (en) 2019-12-04 2022-03-22 Icu Medical, Inc. Infusion pump with safety sequence keypad
US11833329B2 (en) 2019-12-20 2023-12-05 Insulet Corporation Techniques for improved automatic drug delivery performance using delivery tendencies from past delivery history and use patterns
US11551802B2 (en) 2020-02-11 2023-01-10 Insulet Corporation Early meal detection and calorie intake detection
US11547800B2 (en) 2020-02-12 2023-01-10 Insulet Corporation User parameter dependent cost function for personalized reduction of hypoglycemia and/or hyperglycemia in a closed loop artificial pancreas system
US11324889B2 (en) 2020-02-14 2022-05-10 Insulet Corporation Compensation for missing readings from a glucose monitor in an automated insulin delivery system
US11607493B2 (en) 2020-04-06 2023-03-21 Insulet Corporation Initial total daily insulin setting for user onboarding
WO2022020184A1 (en) 2020-07-21 2022-01-27 Icu Medical, Inc. Fluid transfer devices and methods of use
US11684716B2 (en) 2020-07-31 2023-06-27 Insulet Corporation Techniques to reduce risk of occlusions in drug delivery systems
US11135360B1 (en) 2020-12-07 2021-10-05 Icu Medical, Inc. Concurrent infusion with common line auto flush
US11904140B2 (en) 2021-03-10 2024-02-20 Insulet Corporation Adaptable asymmetric medicament cost component in a control system for medicament delivery
US11738144B2 (en) 2021-09-27 2023-08-29 Insulet Corporation Techniques enabling adaptation of parameters in aid systems by user input
US11439754B1 (en) 2021-12-01 2022-09-13 Insulet Corporation Optimizing embedded formulations for drug delivery

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5569186A (en) * 1994-04-25 1996-10-29 Minimed Inc. Closed loop infusion pump system with removable glucose sensor
US20050245904A1 (en) * 2001-12-19 2005-11-03 Medtronic Minimed Inc. Medication delivery system and monitor
US20080172205A1 (en) * 2006-10-26 2008-07-17 Abbott Diabetes Care, Inc. Method, system and computer program product for real-time detection of sensitivity decline in analyte sensors

Family Cites Families (559)

* Cited by examiner, † Cited by third party
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
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
US4431004A (en) 1981-10-27 1984-02-14 Bessman Samuel P Implantable glucose sensor
US4494950A (en) 1982-01-19 1985-01-22 The Johns Hopkins University Plural module medication delivery system
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
CA1226036A (en) 1983-05-05 1987-08-25 Irving J. Higgins Analytical equipment and sensor electrodes therefor
US5509410A (en) 1983-06-06 1996-04-23 Medisense, Inc. Strip electrode including screen printing of a single layer
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
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
US4854322A (en) 1987-02-25 1989-08-08 Ash Medical Systems, Inc. Capillary filtration and collection device for long-term monitoring of blood constituents
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
US5068536A (en) 1989-01-19 1991-11-26 Futrex, Inc. Method for providing custom calibration for near infrared instruments for measurement of blood glucose
EP0385805B1 (en) 1989-03-03 1996-06-05 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
US4986271A (en) 1989-07-19 1991-01-22 The University Of New Mexico Vivo refillable glucose sensor
US5431160A (en) 1989-07-19 1995-07-11 University Of New Mexico Miniature implantable refillable glucose sensor and material therefor
US5264105A (en) 1989-08-02 1993-11-23 Gregg Brian A Enzyme electrodes
US5320725A (en) 1989-08-02 1994-06-14 E. Heller & Company Electrode and method for the detection of hydrogen peroxide
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
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
US5431921A (en) 1990-09-28 1995-07-11 Pfizer Inc Dispensing device containing a hydrophobic medium
US5251126A (en) 1990-10-29 1993-10-05 Miles Inc. Diabetes data analysis and interpretation method
RU2118116C1 (en) 1990-12-12 1998-08-27 Шервуд Медикал Кампани Thermometer for measuring the temperature of body and method of measuring the patient's body temperature (variants)
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
CA2050057A1 (en) 1991-03-04 1992-09-05 Adam Heller Interferant eliminating biosensors
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
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
US5122925A (en) 1991-04-22 1992-06-16 Control Products, Inc. Package for electronic components
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
US5330634A (en) 1992-08-28 1994-07-19 Via Medical Corporation Calibration solutions useful for analyses of biological fluids and methods employing same
WO1994010553A1 (en) 1992-10-23 1994-05-11 Optex Biomedical, Inc. Fibre-optic probe for the measurement of fluid parameters
US5956501A (en) 1997-01-10 1999-09-21 Health Hero Network, Inc. Disease simulation system and method
US5899855A (en) 1992-11-17 1999-05-04 Health Hero Network, Inc. Modular microprocessor-based health monitoring system
US5284425A (en) * 1992-11-18 1994-02-08 The Lee Company Fluid metering pump
ZA938555B (en) 1992-11-23 1994-08-02 Lilly Co Eli Technique to improve the performance of electrochemical sensors
JPH08505967A (en) 1992-11-24 1996-06-25 パヴィリオン・テクノロジーズ・インコーポレイテッド Method and apparatus for operating a neural network with missing and / or incomplete data
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
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
US5582184A (en) 1993-10-13 1996-12-10 Integ Incorporated Interstitial fluid collection and constituent measurement
US5791344A (en) 1993-11-19 1998-08-11 Alfred E. Mann Foundation For Scientific Research Patient monitoring system
US5497772A (en) 1993-11-19 1996-03-12 Alfred E. Mann Foundation For Scientific Research Glucose 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
US5609575A (en) 1994-04-11 1997-03-11 Graseby Medical Limited Infusion pump and method with dose-rate calculation
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
EP0724859B1 (en) * 1995-02-04 1997-11-12 Baumann & Haldi S.A. Personal device for measurement, processing and transmission of substantially physiological data
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
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
US7016713B2 (en) * 1995-08-09 2006-03-21 Inlight Solutions, Inc. Non-invasive determination of direction and rate of change of an analyte
US5665222A (en) 1995-10-11 1997-09-09 E. Heller & Company Soybean peroxidase electrochemical sensor
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
US6790178B1 (en) 1999-09-24 2004-09-14 Healthetech, Inc. Physiological monitor and associated computation, display and communication unit
US5833603A (en) 1996-03-13 1998-11-10 Lipomatrix, Inc. Implantable biosensing transponder
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
ATE234129T1 (en) 1996-06-18 2003-03-15 Alza Corp DEVICE FOR IMPROVING TRANSDERMAL ADMINISTRATION OF MEDICATIONS OR EXTRACTION OF BODY FLUID
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
US5738220A (en) * 1996-09-30 1998-04-14 Pacesetter, Inc. Distal tip protector cap
US6071251A (en) 1996-12-06 2000-06-06 Abbott Laboratories Method and apparatus for obtaining blood for diagnostic tests
US5964993A (en) 1996-12-19 1999-10-12 Implanted Biosystems Inc. Glucose sensor
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
US6293925B1 (en) 1997-12-31 2001-09-25 Minimed Inc. Insertion device for an insertion set and method of using the same
JP3394262B2 (en) 1997-02-06 2003-04-07 セラセンス、インク. Small volume in vitro analyte sensor
US5980708A (en) 1997-02-12 1999-11-09 Champagne; Gilles Y. High sensitivity multiple waveform voltammetric instrument
EP1011426A1 (en) 1997-02-26 2000-06-28 Diasense, Inc. Individual calibration of blood glucose for supporting noninvasive self-monitoring blood glucose
US6862465B2 (en) 1997-03-04 2005-03-01 Dexcom, Inc. Device and method for determining analyte levels
US6001067A (en) 1997-03-04 1999-12-14 Shults; Mark C. Device and method for determining analyte levels
US7899511B2 (en) 2004-07-13 2011-03-01 Dexcom, Inc. Low oxygen in vivo analyte sensor
US6558321B1 (en) 1997-03-04 2003-05-06 Dexcom, Inc. Systems and methods for remote monitoring and modulation of medical devices
US7192450B2 (en) 2003-05-21 2007-03-20 Dexcom, Inc. Porous membranes for use with implantable devices
US6741877B1 (en) 1997-03-04 2004-05-25 Dexcom, Inc. Device and method for determining analyte levels
US20050033132A1 (en) 1997-03-04 2005-02-10 Shults Mark C. Analyte measuring device
US7657297B2 (en) 2004-05-03 2010-02-02 Dexcom, Inc. Implantable analyte sensor
US6554795B2 (en) 1997-03-06 2003-04-29 Medtronic Ave, Inc. Balloon catheter and method of manufacture
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
US5942979A (en) 1997-04-07 1999-08-24 Luppino; Richard On guard vehicle safety warning system
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
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
US7267665B2 (en) 1999-06-03 2007-09-11 Medtronic Minimed, Inc. Closed loop system for controlling insulin infusion
CA2294610A1 (en) 1997-06-16 1998-12-23 George Moshe Katz Methods of calibrating and testing a sensor for in vivo measurement of an analyte and devices for use in such methods
US6056435A (en) 1997-06-24 2000-05-02 Exergen Corporation Ambient and perfusion normalized temperature detector
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
US6088608A (en) 1997-10-20 2000-07-11 Alfred E. Mann Foundation Electrochemical sensor and integrity tests therefor
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
FI107080B (en) 1997-10-27 2001-05-31 Nokia Mobile Phones Ltd measuring device
DE69836979T2 (en) 1997-11-12 2007-11-08 Lightouch Medical, Inc. METHOD FOR NON-INVASIVE ANALYTIC MEASUREMENT
US6579690B1 (en) 1997-12-05 2003-06-17 Therasense, Inc. Blood analyte monitoring through subcutaneous measurement
US7494816B2 (en) 1997-12-22 2009-02-24 Roche Diagnostic Operations, Inc. System and method for determining a temperature during analyte measurement
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
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
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
US6175752B1 (en) 1998-04-30 2001-01-16 Therasense, 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
US8480580B2 (en) * 1998-04-30 2013-07-09 Abbott Diabetes Care 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
DK1077634T3 (en) * 1998-05-13 2003-11-24 Cygnus Therapeutic Systems Monitoring of physiological analytes
US6121611A (en) 1998-05-20 2000-09-19 Molecular Imaging Corporation Force sensing probe for scanning probe microscopy
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
US6558320B1 (en) 2000-01-20 2003-05-06 Medtronic Minimed, Inc. Handheld personal data assistant (PDA) with a medical device and method of using the same
US6248067B1 (en) 1999-02-05 2001-06-19 Minimed Inc. Analyte sensor and holter-type monitor system and method of using the same
US6557756B1 (en) * 1998-09-04 2003-05-06 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
ATE241933T1 (en) 1998-09-30 2003-06-15 Cygnus Therapeutic Systems METHOD AND DEVICE FOR PREDICTING PHYSIOLOGICAL MEASUREMENT VALUES
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
US6591125B1 (en) 2000-06-27 2003-07-08 Therasense, Inc. Small volume in vitro analyte sensor with diffusible or non-leachable redox mediator
JP4469504B2 (en) 1998-10-08 2010-05-26 メドトロニック ミニメド インコーポレイテッド Remote trait monitor system
US6338790B1 (en) 1998-10-08 2002-01-15 Therasense, Inc. Small volume in vitro analyte sensor with diffusible or non-leachable redox mediator
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
ATE269114T1 (en) 1998-11-20 2004-07-15 Univ Connecticut METHOD AND DEVICE FOR CONTROLLING TISSUE IMPLANT INTERACTIONS
EP1144028B1 (en) 1998-11-30 2004-06-23 Novo Nordisk A/S A system for assisting a user in a medical self treatment, said self treatment comprising a plurality of actions
US7436511B2 (en) * 1999-01-22 2008-10-14 Sensys Medical, Inc. Analyte filter method and apparatus
AU3363000A (en) 1999-02-12 2000-08-29 Cygnus, Inc. Devices and methods for frequent measurement of an analyte present in a biological system
US6360888B1 (en) 1999-02-25 2002-03-26 Minimed Inc. Glucose sensor package system
US6424847B1 (en) 1999-02-25 2002-07-23 Medtronic Minimed, Inc. Glucose monitor calibration methods
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
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
US6423035B1 (en) 1999-06-18 2002-07-23 Animas Corporation Infusion pump with a sealed drive mechanism and improved method of occlusion detection
US6654625B1 (en) 1999-06-18 2003-11-25 Therasense, Inc. Mass transport limited in vivo analyte sensor
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
US7317938B2 (en) * 1999-10-08 2008-01-08 Sensys Medical, Inc. Method of adapting in-vitro models to aid in noninvasive glucose determination
WO2001028495A2 (en) 1999-10-08 2001-04-26 Healthetech, Inc. Indirect calorimeter for weight control
US20060091006A1 (en) 1999-11-04 2006-05-04 Yi Wang Analyte sensor with insertion monitor, and methods
WO2001036660A2 (en) 1999-11-15 2001-05-25 Therasense, Inc. Transition metal complexes attached to a polymer via a flexible chain
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
US7369635B2 (en) 2000-01-21 2008-05-06 Medtronic Minimed, Inc. Rapid discrimination preambles and methods for using the same
US6564105B2 (en) 2000-01-21 2003-05-13 Medtronic Minimed, Inc. Method and apparatus for communicating between an ambulatory medical device and a control device via telemetry using randomized data
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
KR100776070B1 (en) * 2000-03-29 2007-11-16 유니버시티 오브 버지니아 페이턴트 파운데이션 Method, system, and computer program product for the evaluation of glycemic control in diabetes from self-monitoring 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
US7181261B2 (en) 2000-05-15 2007-02-20 Silver James H Implantable, retrievable, thrombus minimizing sensors
US6891936B2 (en) 2000-05-31 2005-05-10 Arkray, Inc. Remote data control system and measuring data gathering method
EP1702560B1 (en) * 2000-06-23 2014-11-19 BodyMedia, Inc. System for monitoring health, wellness and fitness
JP4055926B2 (en) * 2000-08-14 2008-03-05 テルモ株式会社 Infusion pump
CA2408338C (en) * 2000-08-18 2009-09-08 Cygnus, Inc. Methods and devices for prediction of hypoglycemic events
US6633772B2 (en) 2000-08-18 2003-10-14 Cygnus, Inc. Formulation and manipulation of databases of analyte and associated values
WO2002016905A2 (en) * 2000-08-21 2002-02-28 Euro-Celtique, S.A. Near infrared blood glucose monitoring system
WO2002024065A1 (en) 2000-09-22 2002-03-28 Knobbe, Lim & Buckingham Method and apparatus for real-time estimation and control of pysiological parameters
WO2002030264A2 (en) 2000-10-10 2002-04-18 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
US6970529B2 (en) 2001-01-16 2005-11-29 International Business Machines Corporation Unified digital architecture
US20040197846A1 (en) 2001-01-18 2004-10-07 Linda Hockersmith Determination of glucose sensitivity and a method to manipulate blood glucose concentration
CN1525834A (en) 2001-01-22 2004-09-01 - Lancet device having capillary action
CN1556716A (en) 2001-02-22 2004-12-22 ���Ͽع����޹�˾ Modular infusion device and method
US6968294B2 (en) 2001-03-15 2005-11-22 Koninklijke Philips Electronics N.V. Automatic system for monitoring person requiring care and his/her caretaker
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
US6698269B2 (en) 2001-04-27 2004-03-02 Oceana Sensor Technologies, Inc. Transducer in-situ testing apparatus and method
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
US6676816B2 (en) * 2001-05-11 2004-01-13 Therasense, Inc. Transition metal complexes with (pyridyl)imidazole ligands and sensors using said complexes
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
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
US6702857B2 (en) 2001-07-27 2004-03-09 Dexcom, Inc. Membrane for use with implantable devices
US20030032874A1 (en) 2001-07-27 2003-02-13 Dexcom, Inc. Sensor head 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
US6827702B2 (en) 2001-09-07 2004-12-07 Medtronic Minimed, Inc. Safety limits for closed-loop infusion pump control
US20030055380A1 (en) * 2001-09-19 2003-03-20 Flaherty J. Christopher Plunger for patient infusion device
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
EP1448489B1 (en) 2001-11-16 2010-08-25 Stefan Ufer Flexible sensor and method of fabrication
WO2003049424A1 (en) * 2001-12-03 2003-06-12 Nikon Corporation Electronic apparatus, electronic camera, electronic device, image display apparatus, and image transmission system
US7729776B2 (en) 2001-12-19 2010-06-01 Cardiac Pacemakers, Inc. Implantable medical device with two or more telemetry systems
US7022072B2 (en) 2001-12-27 2006-04-04 Medtronic Minimed, Inc. System for monitoring physiological characteristics
US7399277B2 (en) 2001-12-27 2008-07-15 Medtronic Minimed, Inc. System for monitoring physiological characteristics
US7184820B2 (en) 2002-01-25 2007-02-27 Subqiview, Inc. Tissue monitoring system for intravascular infusion
US8010174B2 (en) 2003-08-22 2011-08-30 Dexcom, Inc. Systems and methods for replacing signal artifacts in a glucose sensor data stream
US8260393B2 (en) 2003-07-25 2012-09-04 Dexcom, Inc. Systems and methods for replacing signal data artifacts in a glucose sensor data stream
US8364229B2 (en) 2003-07-25 2013-01-29 Dexcom, Inc. Analyte sensors having a signal-to-noise ratio substantially unaffected by non-constant noise
US9247901B2 (en) * 2003-08-22 2016-02-02 Dexcom, Inc. Systems and methods for replacing signal artifacts in a glucose sensor data stream
US7613491B2 (en) 2002-05-22 2009-11-03 Dexcom, Inc. Silicone based membranes for use in implantable glucose sensors
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
US6830558B2 (en) 2002-03-01 2004-12-14 Insulet Corporation Flow condition sensor assembly for patient infusion device
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
US6936006B2 (en) 2002-03-22 2005-08-30 Novo Nordisk, A/S Atraumatic insertion of a subcutaneous device
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
US7713214B2 (en) 2002-04-19 2010-05-11 Pelikan Technologies, Inc. Method and apparatus for a multi-use body fluid sampling device with optical analyte sensing
US7410468B2 (en) 2002-04-19 2008-08-12 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US7153265B2 (en) 2002-04-22 2006-12-26 Medtronic Minimed, Inc. Anti-inflammatory biosensor for reduced biofouling and enhanced sensor performance
US20040153032A1 (en) 2002-04-23 2004-08-05 Garribotto John T. Dispenser for patient infusion device
CN1516562A (en) 2002-04-25 2004-07-28 松下电器产业株式会社 Dosage determination support device, syringe, and health-care support system
GB2388716B (en) 2002-05-13 2004-10-20 Splashpower Ltd Improvements relating to contact-less power transfer
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
US7018360B2 (en) * 2002-07-16 2006-03-28 Insulet Corporation Flow restriction system and method for patient infusion device
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
US7278983B2 (en) 2002-07-24 2007-10-09 Medtronic Minimed, Inc. Physiological monitoring device for controlling a medication infusion device
EP2327359B1 (en) 2002-08-13 2015-01-21 University Of Virginia Patent Foundation Method, system, and computer program product for processing of self-monitoring blood glucose (smbg) data to enhance diabetic self-management
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
US7144384B2 (en) * 2002-09-30 2006-12-05 Insulet Corporation Dispenser components and methods for patient infusion device
US7128727B2 (en) * 2002-09-30 2006-10-31 Flaherty J Christopher Components and methods for patient infusion device
AU2003287073B2 (en) 2002-10-11 2009-01-08 Becton, Dickinson And Company System and method for initiating and maintaining continuous, long-term control of a concentration of a substance in a patient using a feedback or model-based controller coupled to a single-needle or multi-needle intradermal (ID) delivery device
AU2003287159A1 (en) 2002-10-15 2004-05-04 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
GB0226648D0 (en) 2002-11-15 2002-12-24 Koninkl Philips Electronics Nv Usage data harvesting
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
AU2003303597A1 (en) 2002-12-31 2004-07-29 Therasense, 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
US9872890B2 (en) * 2003-03-19 2018-01-23 Paul C. Davidson Determining insulin dosing schedules and carbohydrate-to-insulin ratios in diabetic patients
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
AU2004232289A1 (en) 2003-04-18 2004-11-04 Insulet Corporation User interface for infusion pump remote controller and method of using the same
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
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
US7761130B2 (en) 2003-07-25 2010-07-20 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
US7460898B2 (en) 2003-12-05 2008-12-02 Dexcom, Inc. Dual electrode system for a continuous analyte sensor
US7074307B2 (en) 2003-07-25 2006-07-11 Dexcom, Inc. Electrode systems for electrochemical sensors
US7424318B2 (en) 2003-12-05 2008-09-09 Dexcom, Inc. Dual electrode system for a continuous analyte sensor
WO2005011520A2 (en) 2003-07-25 2005-02-10 Dexcom, Inc. Oxygen enhancing membrane systems for implantable devices
US8282549B2 (en) 2003-12-09 2012-10-09 Dexcom, Inc. Signal processing for continuous analyte sensor
US7467003B2 (en) 2003-12-05 2008-12-16 Dexcom, Inc. Dual electrode system for a continuous analyte sensor
US7108778B2 (en) 2003-07-25 2006-09-19 Dexcom, Inc. Electrochemical sensors including electrode systems with increased oxygen generation
US20050176136A1 (en) 2003-11-19 2005-08-11 Dexcom, Inc. Afinity domain for analyte sensor
US8423113B2 (en) 2003-07-25 2013-04-16 Dexcom, Inc. Systems and methods for processing sensor data
US7778680B2 (en) 2003-08-01 2010-08-17 Dexcom, Inc. System and methods for processing analyte sensor data
US20080119703A1 (en) 2006-10-04 2008-05-22 Mark Brister Analyte sensor
US8275437B2 (en) 2003-08-01 2012-09-25 Dexcom, Inc. Transcutaneous analyte sensor
US7494465B2 (en) 2004-07-13 2009-02-24 Dexcom, Inc. Transcutaneous analyte sensor
US9135402B2 (en) 2007-12-17 2015-09-15 Dexcom, Inc. Systems and methods for processing sensor data
US8845536B2 (en) 2003-08-01 2014-09-30 Dexcom, Inc. Transcutaneous analyte sensor
US8285354B2 (en) * 2003-08-01 2012-10-09 Dexcom, Inc. System and methods for processing analyte sensor data
US7774145B2 (en) 2003-08-01 2010-08-10 Dexcom, Inc. Transcutaneous analyte sensor
US8886273B2 (en) 2003-08-01 2014-11-11 Dexcom, Inc. Analyte sensor
US8626257B2 (en) 2003-08-01 2014-01-07 Dexcom, Inc. Analyte sensor
US8369919B2 (en) 2003-08-01 2013-02-05 Dexcom, Inc. Systems and methods for processing sensor data
US7591801B2 (en) 2004-02-26 2009-09-22 Dexcom, Inc. Integrated delivery device for continuous glucose sensor
US8233959B2 (en) 2003-08-22 2012-07-31 Dexcom, Inc. Systems 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
US7813809B2 (en) 2004-06-10 2010-10-12 Medtronic, Inc. Implantable pulse generator for providing functional and/or therapeutic stimulation of muscles and/or nerves and/or central nervous system tissue
DE10343863A1 (en) 2003-09-23 2005-04-14 Roche Diagnostics Gmbh Method and device for continuously monitoring the concentration of an analyte
JP3612324B1 (en) * 2003-09-29 2005-01-19 株式会社日立製作所 Blood glucose level display method and apparatus
WO2005032362A2 (en) * 2003-09-30 2005-04-14 Roche Diagnostics Gmbh Sensor with increaseed biocompatibility
US20050090607A1 (en) 2003-10-28 2005-04-28 Dexcom, Inc. Silicone composition for biocompatible membrane
AU2004284368B2 (en) 2003-10-29 2008-11-20 Agency For Science, Technology And Research Biosensor
JP2007512588A (en) 2003-10-29 2007-05-17 ノボ・ノルデイスク・エー/エス Medical advice 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
WO2005051170A2 (en) 2003-11-19 2005-06-09 Dexcom, Inc. Integrated receiver for continuous analyte sensor
US20050113886A1 (en) 2003-11-24 2005-05-26 Fischell David R. Implantable medical system with long range telemetry
EP2256493B1 (en) 2003-12-05 2014-02-26 DexCom, Inc. Calibration techniques for a continuous analyte sensor
US20080197024A1 (en) 2003-12-05 2008-08-21 Dexcom, Inc. Analyte sensor
US8364230B2 (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
US8425416B2 (en) 2006-10-04 2013-04-23 Dexcom, Inc. Analyte sensor
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
US8364231B2 (en) 2006-10-04 2013-01-29 Dexcom, Inc. Analyte sensor
US8287453B2 (en) 2003-12-05 2012-10-16 Dexcom, Inc. Analyte sensor
WO2005057173A2 (en) 2003-12-08 2005-06-23 Dexcom, Inc. Systems and methods for improving electrochemical analyte sensors
US7637868B2 (en) 2004-01-12 2009-12-29 Dexcom, Inc. Composite material for implantable device
EP2843848B1 (en) 2004-01-27 2017-11-01 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
US8165651B2 (en) 2004-02-09 2012-04-24 Abbott Diabetes Care Inc. Analyte sensor, and associated system and method employing a catalytic agent
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
US7364592B2 (en) 2004-02-12 2008-04-29 Dexcom, Inc. Biointerface membrane with macro-and micro-architecture
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
ATE427695T1 (en) * 2004-02-26 2009-04-15 Diabetes Tools Sweden Ab METABOLIC MONITORING, METHOD AND DEVICE FOR INDICATING A HEALTH-RELATED CONDITION OF A PERSON
US8808228B2 (en) 2004-02-26 2014-08-19 Dexcom, Inc. Integrated medicament delivery device for use with continuous analyte sensor
DE102004011135A1 (en) 2004-03-08 2005-09-29 Disetronic Licensing Ag Method and apparatus for calculating a bolus amount
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
JP2007535974A (en) 2004-03-26 2007-12-13 ノボ・ノルデイスク・エー/エス Display device for related data of diabetic patients
US6971274B2 (en) 2004-04-02 2005-12-06 Sierra Instruments, Inc. Immersible thermal mass flow meter
US8277713B2 (en) 2004-05-03 2012-10-02 Dexcom, Inc. Implantable analyte sensor
US20050245799A1 (en) 2004-05-03 2005-11-03 Dexcom, Inc. Implantable analyte sensor
WO2005113036A1 (en) * 2004-05-13 2005-12-01 The Regents Of The University Of California Method and apparatus for glucose control and insulin dosing for diabetics
US7118667B2 (en) 2004-06-02 2006-10-10 Jin Po Lee Biosensors having improved sample application and uses thereof
US7289855B2 (en) * 2004-06-09 2007-10-30 Medtronic, Inc. Implantable medical device package antenna
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
US20070100222A1 (en) 2004-06-14 2007-05-03 Metronic Minimed, Inc. Analyte sensing apparatus for hospital use
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
US20060001551A1 (en) * 2004-06-30 2006-01-05 Ulrich Kraft Analyte monitoring system with wireless alarm
US20060001538A1 (en) 2004-06-30 2006-01-05 Ulrich Kraft Methods of monitoring the concentration of an analyte
US20060015020A1 (en) 2004-07-06 2006-01-19 Dexcom, Inc. Systems and methods for manufacture of an analyte-measuring device including a membrane system
US7783333B2 (en) 2004-07-13 2010-08-24 Dexcom, Inc. Transcutaneous medical device with variable stiffness
US8886272B2 (en) 2004-07-13 2014-11-11 Dexcom, Inc. Analyte sensor
US8170803B2 (en) 2004-07-13 2012-05-01 Dexcom, Inc. Transcutaneous analyte sensor
US8565848B2 (en) 2004-07-13 2013-10-22 Dexcom, Inc. Transcutaneous analyte sensor
US8452368B2 (en) 2004-07-13 2013-05-28 Dexcom, Inc. Transcutaneous analyte sensor
US20070045902A1 (en) 2004-07-13 2007-03-01 Brauker James H Analyte sensor
US20080242961A1 (en) 2004-07-13 2008-10-02 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
WO2006024671A1 (en) 2004-09-03 2006-03-09 Novo Nordisk A/S A method of calibrating a system for measuring the concentration of substances in body and an apparatus for exercising the method
US20090247931A1 (en) 2004-09-23 2009-10-01 Novo Nordisk A/S Device for self-care support
JP5049132B2 (en) 2004-11-15 2012-10-17 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ Mobile medical telemetry device with voice indicator
US7237712B2 (en) 2004-12-01 2007-07-03 Alfred E. Mann Foundation For Scientific Research Implantable device and communication integrated circuit implementable therein
US20070010950A1 (en) * 2004-12-03 2007-01-11 Abensour Daniel S Method to determine the degree and stability of blood glucose control in patients with diabetes mellitus via the creation and continuous update of new statistical indicators in blood glucose monitors or free standing computers
ATE545361T1 (en) 2004-12-13 2012-03-15 Koninkl Philips Electronics Nv MOBILE MONITORING
US8545403B2 (en) 2005-12-28 2013-10-01 Abbott Diabetes Care Inc. Medical device insertion
US7731657B2 (en) 2005-08-30 2010-06-08 Abbott Diabetes Care Inc. Analyte sensor introducer 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
US20070027381A1 (en) 2005-07-29 2007-02-01 Therasense, Inc. Inserter 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
US20090082693A1 (en) * 2004-12-29 2009-03-26 Therasense, Inc. Method and apparatus for providing temperature sensor module in a data communication system
US8512243B2 (en) 2005-09-30 2013-08-20 Abbott Diabetes Care Inc. Integrated introducer and transmitter assembly and methods of use
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
WO2006091918A2 (en) 2005-02-23 2006-08-31 Streck, Inc. Process, composition and kit for providing a stable whole blood calibrator/control
US20090076360A1 (en) 2007-09-13 2009-03-19 Dexcom, Inc. Transcutaneous analyte sensor
US20060202805A1 (en) 2005-03-14 2006-09-14 Alfred E. Mann Foundation For Scientific Research Wireless acquisition and monitoring system
US20070071681A1 (en) 2005-03-15 2007-03-29 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
WO2006110193A2 (en) 2005-04-08 2006-10-19 Dexcom, Inc. Cellulosic-based interference domain for an analyte sensor
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
WO2006124716A2 (en) 2005-05-13 2006-11-23 Trustees Of Boston University Fully automated control system for type 1 diabetes
DE602006016266D1 (en) 2005-06-02 2010-09-30 Isense Corp USING MULTIPLE DATA POINTS AND FILTERING IN AN ANALYTICAL SENSOR
US20070033074A1 (en) 2005-06-03 2007-02-08 Medtronic Minimed, Inc. Therapy management system
US20060272652A1 (en) 2005-06-03 2006-12-07 Medtronic Minimed, Inc. Virtual patient software system for educating and treating individuals with diabetes
WO2006133348A2 (en) 2005-06-08 2006-12-14 Philip Michael Sher 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
WO2007007459A1 (en) 2005-07-12 2007-01-18 Omron Healthcare Co., Ltd. Biochemical measuring instrument for measuring information about component of living body accurately
US20070066956A1 (en) * 2005-07-27 2007-03-22 Medtronic Minimed, Inc. Systems and methods for entering temporary basal rate pattern in an infusion device
US7606784B2 (en) * 2005-08-02 2009-10-20 Northrop Grumman Corporation Uncertainty management in a decision-making system
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
US20090227855A1 (en) 2005-08-16 2009-09-10 Medtronic Minimed, Inc. 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
US8965509B2 (en) * 2005-08-31 2015-02-24 Michael Sasha John Methods and systems for semi-automatic adjustment of medical monitoring and treatment
JP2009507224A (en) 2005-08-31 2009-02-19 ユニヴァーシティー オブ ヴァージニア パテント ファンデーション Improving the accuracy of continuous glucose sensors
JP2009506852A (en) 2005-09-09 2009-02-19 エフ.ホフマン−ラ ロシュ アーゲー System, tool, apparatus and program for diabetes treatment
US9072476B2 (en) 2005-09-23 2015-07-07 Medtronic Minimed, Inc. Flexible sensor apparatus
US8113244B2 (en) 2006-02-09 2012-02-14 Deka Products Limited Partnership Adhesive and peripheral systems and methods for medical devices
US9521968B2 (en) 2005-09-30 2016-12-20 Abbott Diabetes Care Inc. Analyte sensor retention mechanism and methods of use
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
CA2622986A1 (en) 2005-10-20 2007-04-26 Big Glucose Ltd. Non-invasive glucose monitoring
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
WO2007056592A2 (en) 2005-11-08 2007-05-18 M2 Medical A/S 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
US20070168224A1 (en) 2005-11-22 2007-07-19 Letzt Alan M Advanced diabetes management system (adms)
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
US8102789B2 (en) 2005-12-29 2012-01-24 Medtronic, Inc. System and method for synchronous wireless communication with a medical device
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
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
US7630748B2 (en) 2006-10-25 2009-12-08 Abbott Diabetes Care Inc. Method and system for providing analyte monitoring
US7618369B2 (en) 2006-10-02 2009-11-17 Abbott Diabetes Care Inc. Method and system for dynamically updating calibration parameters for an analyte sensor
US9392969B2 (en) 2008-08-31 2016-07-19 Abbott Diabetes Care Inc. Closed loop control and signal attenuation detection
US8346335B2 (en) 2008-03-28 2013-01-01 Abbott Diabetes Care Inc. Analyte sensor calibration management
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
US8140312B2 (en) 2007-05-14 2012-03-20 Abbott Diabetes Care Inc. Method and system for determining analyte levels
EP2011283B1 (en) 2006-04-20 2009-11-18 Lifescan Scotland Ltd Method for transmitting data in a blood glucose system and corresponding blood glucose system
US20070255126A1 (en) 2006-04-28 2007-11-01 Moberg Sheldon B Data communication in networked fluid infusion systems
US7496852B2 (en) 2006-05-16 2009-02-24 International Business Machines Corporation Graphically manipulating a database
US7920907B2 (en) 2006-06-07 2011-04-05 Abbott Diabetes Care Inc. Analyte monitoring system and method
US20080177149A1 (en) 2006-06-16 2008-07-24 Stefan Weinert System and method for collecting patient information from which diabetes therapy may be determined
US20070299617A1 (en) 2006-06-27 2007-12-27 Willis John P Biofouling self-compensating biosensor
US20090105560A1 (en) * 2006-06-28 2009-04-23 David Solomon Lifestyle and eating advisor based on physiological and biological rhythm monitoring
US20080058678A1 (en) * 2006-09-05 2008-03-06 Shinichi Miyata Kit for the determination of an analyte in a bodily fluid sample that includes a meter with a display-based tutorial module
US20080057484A1 (en) * 2006-09-05 2008-03-06 Shinichi Miyata Event-driven method for tutoring a user in the determination of an analyte in a bodily fluid sample
US9056165B2 (en) 2006-09-06 2015-06-16 Medtronic Minimed, Inc. Intelligent therapy recommendation algorithm and method of using the same
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
US8478377B2 (en) 2006-10-04 2013-07-02 Dexcom, Inc. Analyte sensor
US8562528B2 (en) 2006-10-04 2013-10-22 Dexcom, Inc. Analyte sensor
US8449464B2 (en) 2006-10-04 2013-05-28 Dexcom, Inc. Analyte sensor
US8447376B2 (en) 2006-10-04 2013-05-21 Dexcom, Inc. Analyte sensor
US8439837B2 (en) 2006-10-31 2013-05-14 Lifescan, Inc. Systems and methods for detecting hypoglycemic events having a reduced incidence of false alarms
US20080139910A1 (en) 2006-12-06 2008-06-12 Metronic Minimed, Inc. Analyte sensor and method of using the same
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
US20080161666A1 (en) 2006-12-29 2008-07-03 Abbott Diabetes Care, Inc. Analyte devices and methods
US7946985B2 (en) 2006-12-29 2011-05-24 Medtronic Minimed, Inc. Method and system for providing sensor redundancy
US7742747B2 (en) 2007-01-25 2010-06-22 Icera Canada ULC Automatic IIP2 calibration architecture
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
JP2011515112A (en) 2007-03-19 2011-05-19 メディンゴ・リミテッド Method for selecting a bolus dose in a drug delivery device
CA2683962C (en) 2007-04-14 2017-06-06 Abbott Diabetes Care Inc. Method and apparatus for providing data processing and control in medical communication system
CA2683930A1 (en) 2007-04-14 2008-10-23 Abbott Diabetes Care Inc. Method and apparatus for providing data processing and control in medical communication system
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
EP2146622B1 (en) 2007-04-14 2016-05-11 Abbott Diabetes Care Inc. Method and apparatus for providing dynamic multi-stage signal amplification in a medical device
EP2146623B1 (en) 2007-04-14 2014-01-08 Abbott Diabetes Care Inc. Method and apparatus for providing data processing and control in medical communication system
EP2146624B1 (en) 2007-04-14 2020-03-25 Abbott Diabetes Care Inc. Method and apparatus for providing data processing and control in medical communication system
US20080269723A1 (en) 2007-04-25 2008-10-30 Medtronic Minimed, Inc. Closed loop/semi-closed loop therapy modification system
US7928850B2 (en) * 2007-05-08 2011-04-19 Abbott Diabetes Care Inc. Analyte monitoring system and methods
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
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
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
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
CA2685167A1 (en) 2007-05-14 2008-11-27 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
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
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
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
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
US7972296B2 (en) 2007-10-10 2011-07-05 Optiscan Biomedical Corporation Fluid component analysis system and method for glucose monitoring and control
US20080300572A1 (en) 2007-06-01 2008-12-04 Medtronic Minimed, Inc. Wireless monitor for a personal medical device system
AU2008262018A1 (en) 2007-06-08 2008-12-18 Dexcom, Inc. Integrated medicament delivery device for use with continuous analyte sensor
EP2166929B1 (en) 2007-06-15 2012-12-19 F. Hoffmann-La Roche AG Visualization of a parameter which is measured on the human body
US9754078B2 (en) 2007-06-21 2017-09-05 Immersion Corporation Haptic health feedback monitoring
CN101730501A (en) * 2007-06-27 2010-06-09 霍夫曼-拉罗奇有限公司 Patient information input interface for a therapy system
ES2715277T3 (en) 2007-06-29 2019-06-03 Hoffmann La Roche Apparatus and method for remotely controlling an ambulatory medical device
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
WO2009018058A1 (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
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
US8834366B2 (en) 2007-07-31 2014-09-16 Abbott Diabetes Care Inc. Method and apparatus for providing analyte sensor calibration
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
US20090063402A1 (en) 2007-08-31 2009-03-05 Abbott Diabetes Care, Inc. Method and System for Providing Medication Level Determination
DE102007047351A1 (en) 2007-10-02 2009-04-09 B. Braun Melsungen Ag System and method for monitoring and controlling blood glucose levels
US8377031B2 (en) 2007-10-23 2013-02-19 Abbott Diabetes Care Inc. Closed loop control system with safety parameters and methods
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
US8290559B2 (en) 2007-12-17 2012-10-16 Dexcom, Inc. Systems and methods for processing sensor data
US20090164190A1 (en) 2007-12-19 2009-06-25 Abbott Diabetes Care, Inc. Physiological condition simulation device and method
US20090164239A1 (en) 2007-12-19 2009-06-25 Abbott Diabetes Care, Inc. Dynamic Display Of Glucose Information
US20090299155A1 (en) 2008-01-30 2009-12-03 Dexcom, Inc. Continuous cardiac marker sensor system
WO2009105337A2 (en) 2008-02-20 2009-08-27 Dexcom, Inc. Continuous medicament sensor system for in vivo use
EP2252196A4 (en) 2008-02-21 2013-05-15 Dexcom Inc Systems and methods for processing, transmitting and displaying sensor data
US20090242399A1 (en) 2008-03-25 2009-10-01 Dexcom, Inc. Analyte sensor
US8396528B2 (en) 2008-03-25 2013-03-12 Dexcom, Inc. Analyte sensor
US20090247855A1 (en) 2008-03-28 2009-10-01 Dexcom, Inc. Polymer membranes for continuous analyte sensors
US20090259118A1 (en) 2008-03-31 2009-10-15 Abbott Diabetes Care Inc. Shallow Implantable Analyte Sensor with Rapid Physiological Response
US8600682B2 (en) 2008-04-04 2013-12-03 Hygieia, Inc. Apparatus for optimizing a patient's insulin dosage regimen
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
US8734422B2 (en) 2008-08-31 2014-05-27 Abbott Diabetes Care Inc. Closed loop control with improved alarm functions
US9943644B2 (en) 2008-08-31 2018-04-17 Abbott Diabetes Care Inc. Closed loop control with reference measurement and methods thereof
US20100057040A1 (en) 2008-08-31 2010-03-04 Abbott Diabetes Care, Inc. Robust Closed Loop Control And Methods
US20100095229A1 (en) * 2008-09-18 2010-04-15 Abbott Diabetes Care, Inc. Graphical user interface for glucose monitoring system
WO2010033724A2 (en) 2008-09-19 2010-03-25 Dexcom, Inc. Particle-containing membrane and particulate electrode for analyte sensors
US8986208B2 (en) 2008-09-30 2015-03-24 Abbott Diabetes Care Inc. Analyte sensor sensitivity attenuation mitigation
US9320470B2 (en) 2008-12-31 2016-04-26 Medtronic Minimed, Inc. Method and/or system for sensor artifact filtering
US20100198142A1 (en) 2009-02-04 2010-08-05 Abbott Diabetes Care Inc. Multi-Function Analyte Test Device and Methods Therefor
EP2419015A4 (en) 2009-04-16 2014-08-20 Abbott Diabetes Care Inc Analyte sensor calibration management
EP2425210A4 (en) 2009-04-28 2013-01-09 Abbott Diabetes Care Inc Dynamic analyte sensor calibration based on sensor stability profile
US20110027458A1 (en) * 2009-07-02 2011-02-03 Dexcom, Inc. Continuous analyte sensors and methods of making same
BR112012003078A2 (en) 2009-08-17 2019-09-24 Univ California interrogable external sensor system for obtaining one or more biological characteristics of a patient's body internal tissue surface or region, method for obtaining one or more biological characteristics of a patient's internal tissue surface or region, transdermal sensor system for obtaining one or more biological characteristics of a patient's internal tissue region, method for obtaining one or more biological characteristics of a patient's internal tissue region, and interrogable sensor system for obtaining one or more biological characteristics of an internal tissue region of a patient
CN102724913A (en) * 2009-09-30 2012-10-10 德克斯康公司 Transcutaneous analyte sensor
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
US20110208027A1 (en) 2010-02-23 2011-08-25 Roche Diagnostics Operations, Inc. Methods And Systems For Providing Therapeutic Guidelines To A Person Having Diabetes
WO2011163519A2 (en) 2010-06-25 2011-12-29 Dexcom, Inc. Systems and methods for communicating sensor data between communication devices
US10231653B2 (en) * 2010-09-29 2019-03-19 Dexcom, Inc. Advanced continuous analyte monitoring system
EP3744249A1 (en) 2010-10-27 2020-12-02 Dexcom, Inc. Continuous analyte monitor data recording device operable in a blinded mode

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5569186A (en) * 1994-04-25 1996-10-29 Minimed Inc. Closed loop infusion pump system with removable glucose sensor
US20050245904A1 (en) * 2001-12-19 2005-11-03 Medtronic Minimed Inc. Medication delivery system and monitor
US20080172205A1 (en) * 2006-10-26 2008-07-17 Abbott Diabetes Care, Inc. Method, system and computer program product for real-time detection of sensitivity decline in analyte sensors

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3131464A4 (en) * 2014-04-15 2017-12-27 Insulet Corporation Monitoring a physiological parameter associated with tissue of a host to confirm delivery of medication
US10441717B2 (en) 2014-04-15 2019-10-15 Insulet Corporation Monitoring a physiological parameter associated with tissue of a host to confirm delivery of medication
EP3804786A1 (en) * 2014-04-15 2021-04-14 Insulet Corporation Monitoring a physiological parameter associated with tissue of a host to confirm delivery of medication
US11383034B2 (en) 2014-04-15 2022-07-12 Insulet Corporation Monitoring a physiological parameter associated with tissue of a host to confirm delivery of medication
US11241532B2 (en) 2018-08-29 2022-02-08 Insulet Corporation Drug delivery system with sensor having optimized communication and infusion site

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