CN103596491B - Utilize the physiological compensation effects method of mobile communications device - Google Patents

Abstract

The invention discloses and be capable of utilizing the physiology monitoring of mobile communications device and can allow for the detection of motion artifacts so that the result of report has the system and method for acceptable quality.

Description

Utilize the physiological compensation effects method of mobile communications device

Background technology

Present invention relates in general to physiological compensation effects, in particular it relates to utilize the physiological parameter of mobile communications device to supervise Survey method.

Need a kind of easy of use, accurately and can be with domestic or the low cost physiology monitoring solution used under situation of movement Certainly scheme.Smart phone just becomes to become more and more popular, from strength to strength and have and can be used to capture from the external world Information, process and utilize the multiple sensors of radio communication remote transmission information in real time.This makes them need not to add Become the ideal chose of the physiological monitor of ' carrying with ' in the case of hardware, and remotely monitor application in many medical science Their potentiality of aspect research.

The optical video monitoring utilizing the skin that digital camera carries out comprises and changes with the trickle color caused by heart signal Become relevant information and can regard as and comprise fluctuating signal (pulsatile signal).Assuming that utilize White LED to move electricity Words flash of light (mobile phone flash) illuminate a region, and the imaging of the type can be described as reflecting light plethysmograph (reflection photoplethysmographic) (PPG) imaging.Can dynamically comprising by HR signal that PPG captures Can be used to detect the information of other physiological condition.

Motion artifacts (Motion artifact) can affect the result of standard PPG.In mobile device with there is no physical unit Guarantee being stably connected with of as there is pulse blood oxygen instrument clip (pulse-oximeter clip) or ekg electrode situation In the case of, motion artifacts can be of much attention.Need the life of a kind of mobile communications device utilizing and allowing detection motion artifacts The system and method for reason monitoring.

Summary of the invention

The invention discloses one can utilize mobile communications device carry out physiology monitoring and allow to detect motion artifacts So that the result of report has the system and method for acceptable quality.

In one or more embodiments, the present invention includes carrying mobile communications device for the method for physiological compensation effects Supply physical signs signal, utilize mobile communications device to analyze physical signs signal thus obtain the survey of one or more physiological parameter Value and utilize mobile communications device detection impact of motion artifacts sentencing in the measured value of one or more physiological parameters Determine whether retain this measured value.

Also disclose other embodiments and the situation of the method for the present invention.

In one or more embodiments of the system of the present invention, system includes physical signs sensing assembly (sensing Device) and mobile communications device, wherein mobile communications device has analysis physical signs signal thus obtains one or more physiology The analytic unit of the measured value of parameter and detection fortune of the impact of motion artifacts in the measured value of one or more physiological parameters Dynamic artifact detection components.

Also disclose other embodiments and the situation of the system of the present invention.

Also disclosing embodiment and the situation of computer usable medium, wherein computer usable medium has and is contained therein Computer-readable code, wherein computer-readable code causes one or more processor to complete the enforcement of method of the present invention Example.

In order to be best understood from the present invention and other and further object, drawings and detailed description are carried out reference, and Its scope will be indicated in the claims.

Accompanying drawing explanation

Fig. 1 is the flowchart representation of an embodiment of the method for the present invention；

Fig. 1 a is that the schematic flow diagram of the key element of an embodiment of the method for the present invention represents；

Fig. 1 b is that the schematic flow diagram of the key element of another embodiment of the method for the present invention represents；

Fig. 2 a-2c is the signal graph representation of the result of an exemplary embodiment of the method for the present invention；

Fig. 3 a-3c is the signal graph representation of the result of the another exemplary embodiment of the method for the present invention；

Fig. 4 a-4b is the signal graph representation of the result of the further example embodiment of the method for the present invention；

Fig. 5 represents the signal of the time-varying coherent function (TVCF) produced in another exemplary embodiment of the method for the present invention Graph representation；

Fig. 6 a and 6b be the method for the present invention another exemplary embodiment in the signal chart of TVCF under different frequency Represent；

Fig. 7 a-7c represents in another exemplary embodiment of the method for the present invention that the true AF for disparate databases annotates The signal graph representation of the numerical value of (true AF annotation) and frequency change (FV)；And

Fig. 8 represents that the schematic block diagram of an embodiment of the system of the present invention represents.

Detailed description of the invention

Described further below has been the optimal current intended mode of the present invention.Do not take the mode of limited significance Illustrate, but only for the purpose of the General Principle of the explanation present invention, because the scope of the present invention is optimal by claims Ground limits.Although the present invention will be described to have been directed towards each embodiment, but it should be appreciated that claim purport and In the range of the present invention can also exist various further with other embodiment.

For singulative herein, unless the context clearly determines otherwise, otherwise it includes a plurality of referents.

Outside except as otherwise instruction, in specification and claims, represent all numbers of the amount of key element, reaction condition etc. Mesh is understood to be modified by term " about " in all instances.

In order to contribute to understanding the present invention, propose defined below.

" mobile communications device " for herein refers to perform the device of application, and it is portable.In a kind of situation Under, mobile communications device has one or more processor and storage capacity.The example of mobile communications device include mobile phone, Intelligent mobile phone, personal digital assistant etc., but the present invention is not limited in these examples.

" physical signs signal (physiological indicator signal) " for herein refers to may be used for obtaining Obtain the signal of the measured value of one or more physiological parameters.The example of physical signs signal includes that light plethysmograph (PPG) is believed Number, the color video frequency image that obtains of a part for electrocardiogram (EKG) signal and the health from main body is (such as, but not limited to utilization Photographing unit in mobile communications device obtains), they show as reflected P PG image, but the present invention is not limited only to these examples.

" volatibility (Volatility) " for herein refers to such as by kurtosis (kurtosis) and other statistical measures The measured value of the probability obtaining extreme value future that measured value obtains.

" eliminate trend (Detrending) " for herein refer to find out to seasonal effect in time series optimum polynomial matching and from This time series deducts the process of this optimum polynomial matching.

" SpO2 " for herein refers to the measured value of the quantity of the oxygen carried by the erythrocyte in blood.SpO2 generally with The form of percentage ratio is given and measures oxygen saturation.

In one or more embodiments, the method for the present invention of physiological compensation effects includes mobile communications device Physical signs signal (step 5, Fig. 1) is provided, utilizes mobile communications device to analyze physical signs signal thus obtains one or many The measured value (step 10, Fig. 1) of individual physiological parameter and utilize mobile communications device to detect in one or more physiological parameters The impact of motion artifacts determine whether to retain this measured value (step 12, Fig. 1) in measured value.

In one case, can be by placing the health of main body on the object lens of photographing unit in a mobile communication device A part also obtains the video image of this part of health of main body thus provides physical signs signal.In another case, Can be by such as exterior light plethysmograph (PPG) sensor or the outside such Shellfish-based Bioelectric Sensor of electrocardiography transducer Physical signs signal is provided.Should be noted that and provide other method of physical signs signal within the scope of the invention.

Motion artifacts

Disclosed below for detecting the impact of motion artifacts in the measured value of one or more physiological parameters and judging Whether retain an embodiment of the method for this measured value.Should be noted that other embodiments is within the scope of the invention.

In the embodiment shown in Fig. 1 a, the method for the impact for detecting motion artifacts includes that pretreatment is surveyed from physiology The fragment (segment) (15, Fig. 1 a) of the signal of value (20, Fig. 1 a), obtain one of volatibility of the fragment of pretreatment or The numerical value (25, Fig. 1 a) of multiple indexs and according to the numerical value of one or more indexs of volatibility and predetermined threshold value Relatively determine whether not deposit noise/motion artifacts.If noise/motion artifacts does not exists, then this fragment is included in relevant meter In calculation amount, (40, Fig. 1 a) and method forward another fragment (50, Fig. 1 a) to, and premise is that another fragment can be used.If noise/motion Artifact exists, for most of physiological parameters, then abandon this fragment (45, Fig. 1 a) and method forward to another fragment (50, figure 1a), premise is that another fragment can be used.For the measured value of instruction of losing blood, as shown in Figure 1 b, the fragment deadline to pretreatment Frequency spectrum analyzes (30, Fig. 1 b) and by the predetermined measured value of temporal frequency analysis of spectrum and predetermined measured value Threshold value compares (35, Fig. 1 b).If predetermined measurement is in the range of being determined by the threshold value of predetermined measurement, then This fragment is included in relevant amount of calculation interior (40, Fig. 1 b) and method forwards another fragment to, and premise is that another fragment can be used (50, Fig. 1 b).If predetermined measurement in the range of being determined by the threshold value of predetermined measurement, does not then abandon fragment (45, Fig. 1 b) and method forward another fragment (50, Fig. 1 b) to, and premise is that another fragment can be used.

In one case, the measured value of the volatibility in embodiment disclosed above includes kurtosis.At another kind In the case of, the measured value of volatibility includes comentropy (Shannon entropy).In still another case, the measurement of volatibility Value utilizes both kurtosis and comentropy.

In order to be further elucidated with the present invention, following description is for detecting the exemplary enforcement of the application of the method for motion artifacts Example.Though it should be noted that the present invention is not limited only to these exemplary embodiments.

The experimental program of one exemplary embodiment

As follows to the PPG signal testing algorithm obtained from two distinct sights.

1. involuntary movement (Involuntary movement): in clinical setting (clinical setting), Lie on the back the multiple location PPG signal that 10 healthy volunteers are recorded under quiescent conditions 5 to the 20 minutes analysis for us.Point The data of analysis are to simulate a part for experiment of losing blood, baseline and lower body negative pressure apply and form, be only from the data of previous condition For this research.Three identical reflection infrared ray PPG probe (MLT1020 are placed at finger, forehead and ear；Beautiful The ADI instrument company (ADI Instruments) of Colorado Springs, the state state of Colorado).Although finger and ear PPG Probe utilizes clip to connect, but forehead probe is covered securely by limpid dressing (clear dressing).Utilize and be equipped with four bridges Amplifier (Quad Bridge Amp) (ML795&L112；ADI instrument company) and the High Pass Filter Cutoff Frequency of 0.01Hz Physiograph (the Powerlab)/16SP data collecting system of (high-pass filter cut-off) is remembered under 100Hz Record PPG signal.In recording process, main body is not limited by doing any kind of motion.

2. voluntary movement: utilize infrared reflection type PPG transducer (TSD200) and there is gain 100 and 0.05-10Hz The biopotential amplifier (PPG100) of cut-off frequency obtains finger PPG signal from 14 healthy volunteers with upright sitting posture. The BIOPAC system house of MP100(California, USA) for obtaining the finger PPG signal under 100Hz.There is no any motion In the case of baseline record after 5 minutes (that is, clean data (clean data)), transported by the left and right of forefinger in PPG data Moving causes motion artifacts, pulse blood oxygen instrument to be placed on forefinger.Instruction main body produces the motion of a time interval, wherein time interval Determine from 10% change to 50%, noise percentage ratio in each minute fragment.Such as, if it is indicated that main body does side-to-side movement 6 seconds, then the fragment of data will comprise the noise of 10%.The noise of each rank is carried out such controlled motion 5 times.? In the program, we utilize the side-to-side movement of the forefinger with PPG clip to cause motion artifacts, this is because side-to-side movement is vertical In the plane of PPG sensor orientation, therefore with up and down or compared with voluntary movement of finger, generate obvious noise.Utilize matrix real Test roomOff-line analysis is from the PPG signal of the record of two schemes.

B. data prediction:

PPG data is divided into 60s fragment and changes PPG data for the every 10s of whole data.Each 60s PPG fragment Through having finite impulse response (FIR) (FIR) band filter on 64 rank of the cut-off frequency of 0.1Hz and 10Hz.In order to illustrate with PPG signal associates and depends on the time-dependent low frequency trend of type of data analysis, uses low or higher order polynomial to eliminate Trend.In order to artifact detects, we use up to 32 rank fitting of a polynomials to eliminate the instability in PPG signal in some cases Dynamically.It is most important that higher order polynomial eliminates using the effectively classification between signal that is clean and that comprise artifact of trend.Right For the temporal frequency analysis of spectrum during determining the second stage of data available, standard 2 rank multinomial eliminates trend It is used on original PPG data (rather than being used in the data with higher order polynomial elimination trend).Utilize low or high order polynomial After the elimination trend of formula matching, zero average PPG signal.Before carrying out computational analysis, in each data slot of visual inspection PPG waveform also divides them into fragment that is clean and that damage.Any kind of breaking-up in pulse characteristic is labeled as breaking-up Fragment.This is done to determine after a while the accuracy of method.

C. the computation and measurement value of artifact detection

After each PPG data fragment of pretreatment, the method for our artifact detection comprises the meter of following two parameter Calculate.

Kurtosis: kurtosis is for describing the data the observed statistical measures around the distribution of meansigma methods.It represents phase For heavy-tailed (the heavy tail) of distribution of normal distribution and spike (peakedness) or light tail (light tail) peace Face degree (flatness).The kurtosis of normal distribution is 3.Dividing of outliers more more than normal distribution tendency (outlier-prone) Cloth has the peak value more than 3；The distribution of less outlier tendency has the peak value less than 3.Peak value is defined as:

$k=\frac{E{(x-\mathrm{\μ})}^4}{{\mathrm{\σ}}^4}---\left(1\right)$

Wherein μ is the meansigma methods of x, and σ is the standard deviation of x, and the expected value of E (t) expression amount t.

Comentropy (SE): SE quantifies have the probability density function (PDF) of how many signals to be different from and is uniformly distributed, therefore provides The probabilistic quantified measures being present in signal.SE may be calculated:

$\mathrm{SE}=-{\mathrm{\Σ}}_{i=1}^k\frac{n\left(i\right)x\ln g\left(T\left(i\right)\right)}{\log \left(\frac{1}{k}\right)}---\left(2\right)$

Wherein i represents binary number (bin number), and p (i) is the probability distribution of signal amplitude.At present, 16bin(k= 16) have been used to obtain the reasonable accurate measurements of SE.

D. the statistical analysis of computation and measurement value:

Data from involuntary movement scheme are carried out nonparametric graceful-Whitney test (nonparametric Mann Whitney test) thus find out the significance level (significance level) (p < 0.05) of SE and totally to breaking-up PPG fragment between kurtosis measured value.Meanwhile, the data from voluntary movement scheme are had the multiple comparisons of Dunne The nonparametric rank test (Kruskal-Wallis test) of rear test thus find out the clean of two kinds of measured values and noise damaged Significance (p < 0.05) between PPG fragment.

E. the detection of motion/noise artifacts

By in the case of being 0.1 at increment by kurtosis numerical value from 0 being changed to 10, in the case of increment is 0.01 by SE Numerical value is changed to 1.0 from 0.5, for from the clean of two schemes and damage SE that the respective group (pool) of PPG fragment obtains with And the colony of kurtosis numerical value carries out experimenter's operating characteristic (receiver-operator characteristic) (ROC) point Analysis.Evaluate kurtosis and the substantially optimal threshold (example of SE of the substantially optimal Sensitivity and Specificity of the detection producing artifact As, with reference to S.H. Parker (S.H.Park) et al. in Korea S's radiology magazine (Korean J Radiol.) the 1-3 month in 2004: Experimenter's operating characteristic (ROC) curve (Receiver Operating Characteristic (ROC) that 11-18 delivers Curve): radiologist puts into practice review (Practical Review for Radiologists), for all purposes in it Hold and be incorporated herein by the way of reference).

The decision rule of the detection of artifact is formulated as follows:

${\mathrm{DK}}_i=\left\{\begin{array}{cc}1& \mathrm{if}{K}_i\&le;K_{\mathrm{Th}}\\ 0& \mathrm{if}{K}_i>K_{\mathrm{Th}}\end{array}\right.---\left(3\right)$

Wherein DK_iRefer to based on i^thKurtosis K of fragment_iArtifact detection judgement.' 1 ' represents clean data, and ' 0 ' Represent and damage data, K_ThRefer to kurtosis threshold value.

${\mathrm{DS}}_i=\left\{\begin{array}{cc}1& \mathrm{if}{\mathrm{SE}}_i\&GreaterEqual;{\mathrm{SE}}_{\mathrm{Th}}\\ 0& \mathrm{if}{\mathrm{SE}}_i<{\mathrm{SE}}_{\mathrm{Th}}\end{array}\right.---\left(4\right)$

Wherein DS_iRefer to based on i^thThe SE SE of fragment_iArtifact detection judgement.' 1 ' represents clean data, and ' 0 ' Represent and damage data.SE_ThRefer to SE threshold value.

Consider kurtosis and SE tolerance that the substantially optimal threshold utilizing the artifact of kurtosis and SE to detect carries out further (metrics) fusion, and quantify the Sensitivity and Specificity of the fusion of both tolerance.Utilize the fusion of kurtosis and SE The decision rule of the detection of artifact is:

${\mathrm{FD}}_i=\left\{\begin{array}{cc}1& \mathrm{if}{\mathrm{DK}}_i+{\mathrm{DS}}_i=2\\ 0& \mathrm{if}{\mathrm{DK}}_i+{\mathrm{DS}}_i\&NotEqual;2\end{array}\right.---\left(5\right)$

Wherein FD_iRefer to based on i^thThe DK of fragment_iAnd DS_iArtifact detection fusion judge.' 1 ' represent clean data and ' 0 ' Represent and damage data.

The temporal frequency analysis of spectrum of the assessment of the noise order of severity

In the second stage (the most just detecting and losing blood) of this embodiment of motion/noise artifacts algorithm, assess noise The order of severity (as shown in Figure 1 b) that dynamically must reach of the signal in HR frequency range to be affected.Specifically, this second Stage determines whether some fragments being considered to comprise artifact may be used for noinvasive and lose blood detection, because these data are not by sternly Important place is polluted.

This stage first-selection requires time for the calculating of frequency analysis, in order to can obtain heart rate band (heart rate band) The amplitude modulation of each time point interior.The AM information of this extraction is used for determining data available as further part describes in detail State.Use the temporal frequency method being referred to as variable frequency complex demodulation method (VFCDM) that will be discussed below, because its One of the highest temporal frequency resolution of offer has been provided.

VFCDM analyze: the exploitation of VFCDM algorithm before this K.H. old (K.H.Chon), S. reach assorted (S.Dash) and K. nine (K.Ju) " IEEE biomedical engineering transactions (IEEE Trans Biomed Eng) " in August, 2009 rolls up the 56, the 8th Phase 2054-63 page " utilize the estimation of the respiratory frequency from photo-plethysmographic diagram data of T/F Power estimation (Estimation of respiratory rate from photoplethysmogram data using time- Frequency spectral estimation) " and the U.S. Patent Application Publication No. of announcement on November 20th, 2008 No. 20080287815, corresponding on May 16th, 2007 submit to the 11/803rd, No. 770 patent application of the U.S. disclosed in, for This two documents is hereby incorporated by by the way of reference by all purposes.Therefore VFCDM operation method is only briefly summarized below Then.

Sinusoidal signal x (t) is regarded as has mid frequency f0, instantaneous amplitude A (t), phase placeWith DC component dc Arrowband vibration (narrow band oscillation) of (t):

x(t)=dc(t)+A(t)cos)2πf₀t+φ(t)) (6)

For given mid frequency, can be by making (6) to be multiplied by_e ^-j2πf0tExtract instantaneous amplitude information A (t) and phase place is believed BreathResult is as follows:

$\begin{array}{cc}z\left(t\right)=x\left(t\right)e^{-j2\mathrm{\&pi;}{f}_{o}t}=\mathrm{dc}\left(t\right)e^{-j2\mathrm{\&pi;}{f}_{o}t}+& \left(\frac{A\left(\mathrm{\&epsiv;}\right)}{2}\right)\end{array},e^{\mathrm{j\&phi;}\left(\mathrm{\&epsiv;}\right)}+\left(\frac{A\left(t\right)}{2}\right)e^{-j(4\mathrm{\&pi;}{f}_{o}t+\mathrm{\&phi;}\left(t\right))}---\left(7\right)$

Pass through e^-j2πf0tLeft side conversion cause the mid frequency f0 of spectrum of z (t) to move to zero frequency.If in (7) Z (t) by having the ideal low-pass filter (LPF) of cut-off frequency (cutoff frequency) fc < fo, then filtration Signal z_ipT () will only comprise relevant component and can extract herein below:

$z_{\mathrm{lp}}\left(t\right)=\frac{A\left(t\right)}{2}{e}^{\mathrm{j\&phi;}\left(t\right)}---\left(8\right)$

A(t)=2|z_lp(t)| (9)

$\mathrm{\&phi;}\left(t\right)={\tan }^{-1}\frac{\mathrm{imag}\left(z_{\mathrm{ip}}\left(t\right)\right)}{\mathrm{real}\left(e_{\mathrm{ip}}\left(t\right)\right)}---\left(10\right)$

Method can readily extend to variable frequency situation: wherein modulating frequency is expressed asFor demodulating Negative exponent item beIt is as follows that the common differential that can utilize phase information obtains instantaneous frequency:

$f\left(t\right)=f_0+\frac{1}{2\mathrm{\&pi;}}\frac{\mathrm{d\&phi;}\left(t\right)}{d\left(t\right)}---\left(11\right)$

Therefore, VFCD method includes two-step method.First, the dominant frequency of fixed frequency complex demodulation techniques identification signal (dominant frequencies), each dominant frequency is converted to mid frequency and to each in mid frequency Application low pass filter (LPF).The cut-off frequency of LPF is less than the cut-off frequency of initial centre frequencies, and to each advantage Frequency application LPF.This generates a series of band-limited signals (band-limited signal).It is each for utilizing Hilbert transform Individual band-limited signal obtain instantaneous amplitude, phase and frequency information and by instantaneous amplitude, phase and frequency information combine thus generate Temporal frequency sequence (TFS).Finally, the second step of VFCDM method is only selection advantage frequency produce high-resolution TFS.

As soon as obtained the TFS of PPG signal by VFCDM method, in the range of the HR band of the TFS extracting VFCDM (HR ± 0.2Hz) the maximum instantaneous amplitude of each time point is as the AMHR component of the PPG of the time varying amplitude (AM) of reflection HR frequency.Not yet There is the initially and finally 5s of the TFS considering AMHR extraction, because temporal frequency sequence has the false change that can produce spectral power The intrinsic end effect (inherent end effect) of the opposite sex.Intermediate value for each PPG Segment evaluation AMHR component damaged (median value).

The determination of the available PPG fragment damaged by not notable artifact:

It it is the clean PPG fragment of each probe site of non-random artifact and random artifact scheme as described above Calculate AMHR intermediate value respectively.Meansigma methods ± the 2*SD of AMHR median overall (median population) is confirmed as each dry The each of which 95% of clean PPG data collection adds up boundary.If the AMHR intermediate value damaging PPG fragment is positioned at the statistics of clean data In boundary, the most respective breaking-up PPG fragment is considered as data available；No person its will be by rejection.Therefore, in Fig. 1 general introduction I The model of algorithm have been designed as comprising wherein the detection of the data available of the artifact in PPG signal and quantization Two separate phases work.With reference to Fig. 1 a, pretreatment (filtration) (55, Fig. 1 a) from the fragment (15, Fig. 1) of the signal of PPG, Evaluate one or more indexs of the volatibility of (60, Fig. 1 a) pretreatment fragment thus according to one or more indexs of volatibility Numerical value and predetermined threshold value relatively determine that noise/motion artifacts does not exists.If noise/motion artifacts is not deposited , then fragment is included in relevant amount of calculation (65, Fig. 1) and method forwards another fragment to, and premise is that another fragment can be used. If noise/motion artifacts exists, analyze for pretreatment fragment deadline frequency spectrum, and pre-by temporal frequency analysis of spectrum First determine the average of measured value AMHR AMHR median overall of clean sample with the threshold value of predetermined measured value Value ± 2* standard deviation (SD) compares.If predetermined measured value is at the model determined by the threshold value of predetermined measured value In enclosing, then in fragment is included in relevant amount of calculation and method forwards another fragment to, premise is that another fragment can be used.If it is pre- The measured value first determined not in the range of being determined by the threshold value of predetermined measured value, then abandons fragment and method forwards to Another fragment, premise is that another fragment can be used.

Heart rate and heart rate variability detection

In one case, physiological measure is heart rate and heart rate variability.In one embodiment, the present invention is used for obtaining The method of the measured value obtaining heart rate and heart rate variability includes (the detection logical operations of beating of beating determining physical signs signal The example of (beat detection algorithm) can be from http://www.Flipcode.com/misc/ BeatDetectionAlgorithms.pdf is available and addressable beats in detection calculations rule on January 17th, 2012 Find, but the present invention be not limited only to such example), determine by interval of fighting (beat to beat interval) and apply three Secondary batten algorithm (cubic spline algorithm) obtains the substantially continuous print of instruction heart rate by blank signal of fighting.

Can apply and be disclosed in entitled RR interval monitoring method and utilize blood pressure cuff (the RR INTERVAL of the method MONITORING METHOD AND BLOOD PRESSURE CUFF UTILIZING SAME), be disclosed on July 7th, 2011 No. 20110166466 patent application of the U.S. in the detection method by variability of fighting, for all purposes, the document with The mode of reference is hereby incorporated by.Furthermore, it is possible to application is disclosed in entitled detection and treatment autonomic nervous system is unbalance Method and apparatus (Method And Apparatus For Detection And Treatment Of Autonomic System Imbalance), the autonomous god that is disclosed in No. 20090318983 patent application of in December, 2009 U.S. of 24 days Through the method for the detection of system imbalance, for all purposes, the document is incorporated herein as reference.

In another case, physiological measure is breathing rate.For obtaining of the method for the measured value of breathing rate Embodiment includes utilizing variable frequency complex demodulation (VFCDM) to obtain the temporal frequency spectrum of physical signs signal and by being extracted in Each time point of heart rate frequency band has the frequency component of peak swing and obtains breathing rate.

In order to be further elucidated with the present invention, the example of the measured value of heart rate introduced below and heart rate variability and breathing rate Property embodiment.Should be noted that and the invention is not restricted to this exemplary embodiment.

In order to compare exemplary embodiment and the traditional method of the present invention, conventional art is utilized to complete experiment thus measured value Heart rate, heart rate variability and breathing rate.By utilizing standard 5-lead electrode to construct (5-lead electrode Configuration) HP78354A acquisition system carries out electrocardiogram (EKG) record.The chest that breathing bellyband ties up to main body is attached Near thus monitor respiratory frequency (Respitrace system, dynamic monitoring company (Ambulatory Monitoring Inc.)). Use LabChart software (AD instrument company) to preserve with the sample rate of 400Hz to breathe and EKG record.

Data are recorded in the spontaneous respiration process of single main body.Start data collection as follows: (1) starts mobile phone and regards Frequently record, (2) start EKG and breathe the note following the trail of (respiration trace) for 10 seconds after starting mobile phone record Record, and (3) put down mobile phone and the left index finger of main body is placed above at camera gun.This process allows data literary composition Part was registered in 1 second.

To be set as 0.2,0.3 and 0.4Hz(12,18 and 24 beats (BPM) per minute) speed complete in single main body Become metronome respiration test.Require that main body is along with metronomic each percussion air-breathing.Metronome record 2 points is carried out for each joint Clock.

For utilizing the measured value of the exemplary embodiment of the present invention, utilize Motorola(Motorola Commmunication company) color change of mobile phone record finger.A left side is placed above at camera gun in the case of opening flash of light The palmar of hands forefinger.In the case of not having to press by additional power, instruction main body makes their finger rest on photographing unit mirror On head, and keep their finger static thus reduce any motion artifacts.With .3gpp file format, the adopting of 24.99fps Sample rate, utilize 720x480 pixel resolution record video.Utilize Pazera free 3gp to AVI transducer 1.3(http: // Www.pazera-software.com/) audio-video that .3gpp video conversion is 720x480 resolution and 25fps is interlocked (AVI) form.At matrix labotstory R2010b(Matlab R2010b) (Mai Si Volco Inc (The Mathworks Inc.)) In AVI video completed all further analyses.

For Experimental Evaluation HR, heart rate variability (HRV) and breathing rate, only use the greenbelt from videograph (green band).The 50x50 pixel carrying out region on the video signal of each frame for greenbelt is average.This signal here claims For green (GREEN).

Utilize self-defined peakvalue's checking algorithm (custom peak detection algorithm) to EKG signal Complete the detection of R-crest value.Utilize conventional operation rule that GREEN signal detection is beaten.Calculate by interval the cubic spline of fighting By fighting, interval to 4Hz thus obtains continuous HR(HREKG and HRGREEN of each signal).Utilize Wei Er odd cycle figure method (Welch periodogrammethod) calculates the power spectral density (PSD) of HR.

Fig. 2 a show in spontaneous respiration process the part 105 of the exemplary GREEN signal obtained.Pulse signal with from arteries and veins Traditional PPG signal that BOLD contrast of fighting obtains is similar to.As shown in Figure 2 b, with the signal one obtained from EKG after R-crest value detects Play peakvalue's checking thus identify HR signal.Meansigma methods ± the SD of HREKG is 92.2 ± 5.3, the meansigma methods ± SD of HRGREEN It is 92.3 ± 5.9.

By moving of HR signal HRGREEN110, the HREKG120 shown in frequency analysis (Fig. 2 c) evaluation Fig. 2 b State.Can be considered as being in low frequency < 0.1Hz by the advantage peak of two kinds of signals.Can be considered as the second peak of two kinds of signals handing over The 3rd peak at the neural scope (sympathetic range) of sense interior (0.04-0.15Hz) and about 0.2Hz represents to be breathed Rate.Compared with HREKG, additional high frequency components considered to be in HRGREEN112, may be from mobile phone record The low sampling frequency of suboptimum.

Breathing rate detects

As old in K.H. (K.H.Chon), S. reach assorted (S.Dash) and K. nine (K.Ju) " the IEEE biology doctor in August, 2009 Learn engineering transactions (IEEE Trans Biomed Eng) " volume the 56, the 8th phase 2054-63 page " utilize temporal frequency Power estimation Estimation (Estimation of respiratory rate from from the respiratory frequency of photo-plethysmographic diagram data Photoplethysmogram data using time-frequency spectral estimation) " and 2008 11 The U.S. Patent Application Publication No. 20080287815 months 20 days announced, corresponding to the U.S. the submitted on May 16th, 2007 Extracting frequency modulation (FM) and amplitude modulation (AM) sequence described in 11/803, No. 770 patent application, this two documents is for all Purpose entirety in the way of reference be hereby incorporated by and for estimating breathing rate (Fig. 3 a&b).By utilizing 0.2, The PSD obtaining breathing tracking in the metronome respiratory in 3 cycles of the 0.3 and 0.4Hz metronome record set confirms Respiratory frequency.Respectively with 0.18 and 0.16,0.30 and 0.32 and 0.40 and 0.38Hz tri-kind of metronome rate estimates utilize FM Following the trail of from breathing and the breathing rate of GREEN signal of sequence.FM sequence 210,220,232 and the breathing of three breathing rates are followed the trail of 212, the PSD of 222,230 is as shown in Figure 3 c.

Oxygen saturation detects

In still other cases, physiological measure is the measured value of oxygen saturation.In one embodiment, by mobile logical The object lens of the photographing unit of T unit are placed above regarding of this part of a part for the health of main body and the health of acquisition main body Frequently Image Acquisition physical signs signal.In this embodiment, the method for the present invention measured value for obtaining oxygen saturation includes Obtain the red component of video image and the mean intensity of blue component of this part of the health of main body, red component average The mean intensity of intensity and blue component respectively constitutes DCRED and DCBLUE, it is thus achieved that red component and the standard deviation of blue component Difference, the standard deviation of red component and blue component respectively constitutes ACRED and ACBLUE, and obtains oxygen saturation by following formula (SpO2) measured value

$\mathrm{SpO}2=A-B\frac{{\mathrm{AC}}_{\mathrm{RED}/}{\mathrm{DC}}_{\mathrm{RED}}}{{\mathrm{AC}}_{\mathrm{BLUE}}/{\mathrm{DC}}_{\mathrm{BLUE}}}.$

In order to be further elucidated with the present invention, the exemplary embodiment of the measured value of oxygen saturation introduced below.It should be noted that Be to the invention is not restricted to this exemplary embodiment.

In order to compare exemplary embodiment and the traditional method of the present invention, complete experiment thus measure oxygen saturation.

Complete to hold one's breath experiment (Breath holding experiment) thus evaluate the oxygen saturation of reduction to two masters The impact of the reported visual sensation of body.The left hand third finger is placed commercial reflectance pulse BOLD contrast (basis SETTM(Radical SETTM), Mai Xin promise company (Masimo)) record SpO2 1 second measured value.Left forefinger tip mobile electricity placed below in main body Words camera gun.On camera gun, finger be placed around black cloth so that sensor with by commercial pulse blood oxygen instrument Radiate is optically isolated.Start to start the data of pulse blood oxygen instrument by verbal order afterwards at mobile phone record and be stored in (data And utilize audio file aligned data file so that it is determined that start time point logging).

Require main body eupnea about 30 seconds, exhale, then hold one's breath until they feel under the weather.Main for each Two continuous print of body record are held one's breath the phase.

Oxygen saturation is monitored

Calculate red (RED) in the equation of the SpO provided above and ratio of blue (BLUE) and by commercialization pulse blood oxygen instrument SpO2 numerical value estimates A and B parameter as being referenced as each main body.For the main body shown in Fig. 4 a, determineIn A and B be respectively 154.5 and 220.3, and for the main body in Fig. 4 b, determine that A and B is 155.7 With 265.5.(in figs 4 a and 4b, the measured value from pulse blood oxygen instrument is described as 310,312, and from the measurement of the present invention Value is described as 320,322.In Fig. 4 a, 4b it can be observed how, the SpO monitored with commercial pulse blood oxygen instrument₂Reduce and seem to cause From the SpO of our calculating that mobile phone record obtains₂The reduction of numerical value.For the main body in Fig. 4 a, according to commercial pulse- BOLD contrast have recorded the minimum SpO of 84%₂Level and utilize following formula to calculate the minima of 81%:

$\mathrm{SpO}2=A-B\frac{{\mathrm{AC}}_{\mathrm{RED}/}{\mathrm{DC}}_{\mathrm{RED}}}{{\mathrm{AC}}_{\mathrm{BLUE}}/{\mathrm{DC}}_{\mathrm{BLUE}}}.$

Although it should be noted that, we complete off-line analysis in above-mentioned exemplary embodiment, it is assumed that mobile phone In available current processing capabilities (available current 1GHz dual core processor), but directly complete on a cellular telephone to analyze also at this In the range of invention.

Lose blood detection

In another case, physiological measure is the measurement lost blood.For obtaining an enforcement of the method measured of losing blood Example includes utilizing variable frequency complex demodulation (VFCDM) to obtain the temporal frequency spectrum of physical signs signal, from temporal frequency spectrum One group of maximum instantaneous amplitude at time sample each time in heart rate frequency band obtains amplitude modulation (AM) and determines whether amplitude modulation subtracts Little, the blood loss reducing instruction main body of amplitude modulation.

For obtaining the exemplary embodiment of the method measured of losing blood entitled " losing blood of submitting on January 21st, 2011 The system and method (SYSTEM AND METHOD FOR THEDETECTION OF BLOOD VOLUME LOSS) of amount detection " No. 61/434,856 provisional application of the U.S. and nanmu reach storehouse Marcel watt add (Nandakumar Selvaraj), gram in David Stauffer G Si Cooley (Christopher G.Scully), Ke Ke H thank jasmine (Kirk H.Shelley), David G Xi Erfuman (David G.Silverman) and Ki H. old (Chon) in August in 2011 30 days-JIUYUE 3 days at U.S.'s horse Sa The 33rd, Boston, Zhu Sai state IEEE EMBS year international conference (33rdAnnual International Conference Of the IEEE EMBS Boston, Massachusetts USA) disclosed in the amplitude modulation utilizing photo-plethysmographic figure from Send out early stage detection (the Early Detection of Spontaneous Blood Loss using Amplitude lost blood Modulation of Photoplethysmogram) disclosed in, all the elements are for all purposes in the way of reference It is hereby incorporated by as entirety.

For obtaining the other embodiments of the method measured of losing blood in WIPO international publication WO2011/050066A2, name It is referred to as " apparatus and method (the Apparatus And Method For of the early stage detection of breathing rate detection and blood loss Respiratory Rate Detection And Early Detection Of Blood Loss Volume) ", be disclosed in Disclosed in the patent documentation on April 28th, 2011, for all purposes, document entirety in the way of reference is incorporated into This.

Atrial fibrillation detects

In other situations, physiological measure is the measurement of atrial fibrillation (atrial fibrillation).For obtaining One embodiment of the method obtaining atrial fibrillation measured value includes: when obtaining by making two time-varying transmission function (TVFT) be multiplied Becoming coherent function, the two time-varying transmission function utilizes two proximity data fragments to obtain, and one of them data slot is as defeated Enter signal, another data slot is as output thus produces a TVTF, produces second by reverse input and output signal TVTF；And determine that whether time-varying coherent function (TVCF) is less than predetermined volume.In another embodiment, determine that time-varying is concerned with Whether function includes obtaining one or more indexs of atrial fibrillation and determining one of atrial fibrillation less than predetermined volume Or whether multiple index exceedes predetermined threshold value.In one case, one or more indexs of atrial fibrillation include time-varying The change of coherent function.In another case, one or more indexs of atrial fibrillation also include comentropy.In another feelings Under condition, utilize experimenter's operating characteristic (ROC) to analyze and determine predetermined threshold value.

Disclosed above in the embodiment of the method obtaining atrial fibrillation measured value, by two time-varying transmission letters The estimation TVCF that is multiplied of number (TVTF).Two neighbouring data slots are utilized to obtain the two TVTF, one of them data slot As input signal, another data slot as output, thus produce a TVTF；Produced by reverse input and output signal Raw 2nd TVTF.Have been found that the TVCF of the generation between two neighbouring normal sinus rhythm fragments shows to run through whole frequency The high coherent value (close to 1) of scope.But, if one of them fragment or two segment portion or completely include AF, then produce Raw TVCF is significantly lower than 1.When TVCF combines with comentropy (SE), for having the MIT-BIH atrial fibrillation of 128 fragments of beating Dynamic (AF) data base (n=23) obtains the AF verification and measurement ratio the most accurately of 97.9%.

In embodiments disclosed above, by the acquisition TVCF that is multiplied of two time-varying transmission functions.In order to show acquisition The utilization of TVTF in TVCF, is first defined as TVCF by nonparametric temporal frequency spectrum:

${\left|\mathrm{\&gamma;}(t,f)\right|}^4=\frac{{|s_{\mathrm{xy}}(t,f)}^2}{s_{\mathrm{xx}}(t,f)s_{\mathrm{yy}}(t,f)}\frac{{\left|s_{\mathrm{yx}}(t,f)\right|}^2}{s_{\mathrm{yy}}(t,f)s_{\mathrm{xx}}(t,f)}---\left(12\right)$

Wherein S_xy(t, f) and S_yx(t, f) express time frequency translation spectrum, S_xx(t, f) and S_yy(t f) represents two respectively The autologous spectrum (auto spectra) of signal x and y.Specifically, when x regard as input and y regard output as time equation (12) In Section 1 be coherent function.Similarly, the Section 2 in equation (12) when y regards that input and x regard output as It it is coherent function.For x as input and y as output linear time-varying (TV) system, according to T/F spectrum TVTF Can obtain as follows:

$H_{x\&RightArrow;y}(t,f)=\frac{s_{\mathrm{xy}}(t,f)}{s_{\mathrm{xx}}(t,f)}---\left(13\right)$

Wherein H_x→y(t f) is the TVTF from input x to output y signal.Similarly, for y as input and x conduct The linear TV system of output, it is possible to obtain TVTF is as follows:

$H_{y\&RightArrow;x}(t,f)=\frac{s_{\mathrm{yx}}(t,f)}{s_{\mathrm{yy}}(t,f)}---\left(14\right)$

Therefore, obtain time-varying magnitude (time-varying magnitude) by making two transmission functions be multiplied,

|H_x→y(t, f) H_y→x(t, f)

Assuming that the relation of (15), high-resolution TVCF can be obtained from arma modeling:

$y\left(n\right)=-\underset{i=1}{\overset{p_1}{\mathrm{\&Sigma;}}}a(n,e)y(n-i)+\underset{j=D}{\overset{Q_1}{\mathrm{\&Sigma;}}}b(n,j)x(n----(16-1)$

$x\left(n\right)=-\underset{i=1}{\overset{p_2}{\mathrm{\&Sigma;}}}\mathrm{\&alpha;}(n,i)x(n-i)+\underset{j=D}{\overset{Q_1}{\mathrm{\&Sigma;}}}\mathrm{\&beta;}(n,j)y(n-j)---(16-2)$

Wherein (16-1) represents that y (n) is as output and x (n) conduct input.Similarly, (16-2) represents x (n) conduct Output and y (n) are as input.Assuming that the arma modeling of (16), it is possible to obtain two transmission functions (15) are as follows:

$\begin{array}{c}{H}_{x\&RightArrow;y}(n,e^{\mathrm{jiv}})=\frac{B(n,e^{\mathrm{jiv}})}{A(n,e^{\mathrm{jiv}})}=\frac{{\mathrm{\&Sigma;}}_{i=D}^{Q_i}b(n,l)e^{-\mathrm{jiv}}}{1+{\mathrm{\&Sigma;}}_{i=1}^{p_i}a(n,i)e^{-\mathrm{jiv}}}\\ H_{y\&RightArrow;x}(n,e^{\mathrm{jiv}})=\frac{\mathrm{\&beta;}(n,e^{\mathrm{jw}})}{\mathrm{\&alpha;}(n,e^{\mathrm{jw}})}=\frac{{\mathrm{\&Sigma;}}_{i=0}^{Q_2}\mathrm{\&beta;}(n,j)e^{-\mathrm{jwi}}}{1+{\mathrm{\&Sigma;}}_{i=1}^{p_1}\mathrm{\&alpha;}(n,i)e^{-\mathrm{jwi}}}\end{array}---\left(17\right)$

Finally, TVCF can be obtained by making two transmission functions as described in (17) be multiplied.For parameter estimation, can Searching for (TVOPS) criterion in order to by time-varying parameters optimization, when the physiological signal application different to many, this criterion demonstrates standard Really property.For the physiological signal considered, TVOPS has shown that and searches for than AIC, minimum description length (MDL) and fast orthogonal Criterion is more accurate.For TVOPS, time-varying coefficient expands one group of basic function to.Have shown that Legnedre polynomial is before Catch the dynamic wisdom steadily changed in time to select.

AF detects: the change of TVCF

AF is detected, utilizes following arma modeling to be formulated two neighbours with the length being expressed as seg Closely beat fragment:

$\begin{array}{c}{s}_{i+1:i+\mathrm{seg}}=-\underset{i=1}{\overset{p_1}{\mathrm{\&Sigma;}}}a(n,i)s_{i+1i+\mathrm{seg}}+\underset{j=0}{\overset{Q_1}{\mathrm{\&Sigma;}}}b(n,l)s_{i+\mathrm{seg}+1i2\mathrm{seg}}(n-j)\\ s_{i+\mathrm{seg}+1i+2\mathrm{seg}}\left(n\right)=-\underset{i=1}{\overset{p_1}{\mathrm{\&Sigma;}}}a(n,i)s_{i+\mathrm{seg}+1:i+2-\mathrm{seg}}(n-i)+\underset{j=0}{\overset{Q_1}{\mathrm{\&Sigma;}}}+\underset{j=0}{\overset{Q_1}{\mathrm{\&Sigma;}}}\mathrm{\&beta;}(n,j)s_{i+1-i+\mathrm{seg}}\end{array}---\left(18\right)$

Wherein S_i+1i+seg(n) and S_{I+seg ten}1_i+2seg ⁽N) it is respectively from (i+1)^thTo (i+seg)^thWith from (i+seg+l)^thArrive (i+2·seg)^thTwo neighbouring RR sequences interval time.By (18) are substituted into (17), it is thus achieved that two transmission functions, and And by the acquisition TVCF that is multiplied of two TVCF.

In order to be further elucidated with the present invention, the exemplary embodiment of the measurement of atrial fibrillation introduced below.It should be noted that It is to the invention is not restricted to this exemplary embodiment.

Utilize fragment of beating to four data library test detection calculations rules 128 times: MIT-BIH AF data base, MIT- BIH normal sinus rhythm (NSR) data base (n=18), MIT-BIH arrhythmia data base (n=48) and clinical 24-hour Hall Special AF data base (n=15).

In order to illustrate that AF detects, the main body 8455 for MIT-BIH AF data base is utilized to have single order Legendre function ARMA(P1=5, Q1=5) calculate TVCF.Single order Legnedre polynomial is used as to cause that MIT-BIH's AF data base (N=23) is the most accurate Really this selection of property.The rank finding optimal arma modeling are P1=5, Q1=5 in the case of seg=128, and it will be at further part Describe in detail.The 128 of conversion of being beaten for 128 times after use is beaten fragment.Using 64 FFT, it causes the frequency of 0.0156Hz Rate resolution.Fig. 5 represents that the TVCF(according to each generation beaten with normalized frequency assumes the Nyquist frequency of 0.5Hz Rate).As it is shown in figure 5, TVCF numerical value is close in the whole frequency range of two neighbouring normal sinus rhythm (NSR) data slots One.But, when one or two segment portion or when completely including AF, TVCF numerical value is obviously reduced.

As shown in Figure 5, it can be observed that when patient is at AF, TVCF numerical value is for different frequency change greatly.That is, AF Time, altofrequency tends to having relatively low coherent value (seeing Fig. 6 a, 6b) than lower frequency.For this phenomenon detailed further, institute It is shown as and is selecting some TVCF numerical value according to the time in Fig. 6 (a) from the various frequencies of Fig. 5.Fig. 6 (b) represents according to AF and NSR Each normalized frequency of data base and each 128 meansigma methods of corresponding TVCF beating fragment.It is right to should be noted that In AF data, TVCF numerical value is at low frequencies close to one, but they are quickly down to low value when frequency increases.But, for NSR data, TVCF is being almost constant (slightly reducing) for all frequencies at unit amount.This can be by the choosing of AF The arma modeling item selected includes major part oneself and delay (such as, x (n), x (n-i), y (n) and the y (n-of the delayed item of one L)) the fact illustrates, therefore, as expected, TVCF numerical value will only be under low frequency high and when frequency increases Become relatively low.It is further noted that from the left-hand component of Fig. 6 the change observing TVCF numerical value for AF at a relatively high but for NSR is almost constant.

Observation based on above-mentioned the latter, the change of the TVCF running through whole frequency range by inspection completes AF and detects.Right Beat in each, between all frequencies, calculate the change of the TVCF numerical value being referred to as frequency change (FV).Utilize FV-TVCF, right Whole MIT-BIH AF data base investigates AF and detects performance.

Referring now to Fig. 7 A and 3B, it show three typical body 4048,735 and 7162 of MIT-BIH AF data base FV-TVCF numerical value and actual AF annotation.In Fig. 7 (a), data set 4048 comprises and has 206,66,37,34,388,40 and Seven AF outbreak of the length that 42 times beat, and the numerical value of FV-TVCF AF occurs beat in increase.In Fig. 7 (b), Data set 735 comprise there is 332 times AF outbreak of the length beaten and for data set 7162, AF outbreak continue shown in Whole time slice.FV-TVCF numerical value reflects this phenomenon by never returning value of zero.

Ectopic beat elimination and comentropy combine

Relatively low TVCF numerical value is also resulted in including too early or ectopic beat NSR fragment.In order to reduce too early and dystopy The impact beaten, we eliminate exceptional value and filter ectopic beat.Putting it briefly, too early or ectopic beat can be by normal Short-long RR sequence of their labelling (signature) between RR interval is verified.For each RR in time series Interval, calculating ratio RR (i)/RR (i-1), wherein RR (i) is that i & lt (ith) is beaten, and when meeting three below condition Eliminate RR (i) and RR (i+l): 1) RR (i)/RR (i-1)<perc1，2）RR ( i+1 ) /RR ( i )>perc99 and 3) RR (i+1)/ RR (i+2) > perc25, wherein percl, perc25 and perc99 are the based on RR interval numerical value the histogrammic 1st, the 25th respectively With the 99th percentiles.

(19) comentropy (SE) in is also combined with FV-TVCF, thus increases the accuracy of AF detection.SE has represented It is the reliable detector of AF and according to estimation SE calculated below:

$\mathrm{SE}=-\underset{u=1}{\overset{N_{\mathrm{bin}}}{\mathrm{\&Sigma;}}}p\left(u\right)\frac{\log \left(p\left(u\right)\right)}{\log \left(\frac{1}{N_{\mathrm{bin}}}\right)}---\left(19\right)$

Notice when selecting N_binN is selected according to fragment length when=16_binTo realize optimal accuracy.

Detector optimization

In one embodiment, the condition of AF detection can be by simple logic and condition (simple logical AND Condition) be given:

If (FV >=TH_var)AND(SE≥TH_SE), then it is classified as AF.

Otherwise it is classified as non-AF.

THvar and TH_SEIt is the threshold value of variance and comentropy respectively, and selects THvar and TH based on optimal accuracy_SE； Specifically, we use experimenter's operating characteristic (ROC) to analyze.For THvar and TH_SEEach combine, find out true positives (True Positive) (TP), true negative (True Negative) (TN), false positive (False Positive) (FP) and vacation The quantity of negative (FalseNegative) (FN), and use it for accuracy (TP+TN)/(TP+ of MIT-BIH AF data base TN+FP+FN).Additionally, calculate susceptiveness TP/ (TP+FN) and specificity T N/ (TN+FP).By changing the order of arma modeling This process is repeated with the length of fragment.Notice by setting P1=Q1 restriction arma modeling order.There is each not finding out Model sequence and THvar and TH of fragment length with quantity_SEAfter numerical value, to from the data base of MIT-BIH and clinical AF The parameter that database application is identical.

In another embodiment for the method obtaining atrial fibrillation measured value, apply and be spaced monitoring side at entitled RR Method and utilize the method blood pressure cuff, be published in No. 20110166466 patent application of the U.S. on July 7th, 2011 public The root-mean-square (Root Mean Square of Successive Differences) (RMSSD) utilizing successive difference opened The method, this patent application for all purposes in the way of reference entirety be hereby incorporated by.

In one or more embodiments, the present invention includes physical signs sensing for the system of physiological compensation effects Assembly (sensor) and mobile communications device, wherein mobile communications device have analysis physical signs signal thus obtain one or The analytic unit of the measured value of multiple physiological parameters and detection motion artifacts in the measured value of one or more physiological parameters The movement artifact detection assembly of impact.

In one case, mobile communications device includes that one or more processor and one or more computer can be with being situated between Matter, wherein computer usable medium has the computer-readable code being contained therein, and this computer-readable code causes process Device is analyzed physical signs signal thus is obtained the measured value of one or more physiological parameter detecting and join at one or more physiology The impact of motion artifacts in the measured value of number.In one or more embodiments, computer-readable code causes processor to be implemented Said method.

Should be noted that to implement analytic unit and/or movement artifact detection assembly, such as, use ASIC or FPGA The other embodiments of such mobile communications device is within the scope of the invention.

Fig. 8 is that the block diagram of an embodiment of the system of the present invention represents.With reference to Fig. 8, in embodiment shown wherein, Mobile communication system 280 includes processor 250 and one or more memorizer 260.Physical signs sensing assembly (sensing Device) 270 pairs of mobile communications devices 280 provide physical signs signal.Sensor 270 can be light plethysmograph (PPG) sensing Device or electrocardiogram (EKG) sensor.In the embodiment shown in fig. 8, mobile communications device 280 can also be carried by photographing unit 265 For physical signs signal, wherein photographing unit 265 is as object lens 267.One or more memorizeies 260 have the meter being contained therein Calculation machine available code, this computer available code causes processor 250 to analyze physical signs signal thus obtains one or more The measured value of physiological parameter also detects the impact of motion artifacts in the measured value of one or more physiological parameters.A kind of or many In the case of Zhong, computer-readable code causes processor 250 to complete the enforcement of said method.

One or more memorizeies 260 represent the computer usable medium with the computer-readable code being contained therein An embodiment, wherein computer-readable code cause processor implement the present invention method.The foregoing describe the present invention's The embodiment of method, and computer-readable code can cause processor to implement those embodiments.

In the embodiment shown in fig. 8, mobile communications device 280 also includes that antenna 265, antenna 265 are allowed by one Or multiple multiple wireless protocols or cover the communication of wireless network.Although it should be noted that, sensor 270 show and is directly connected to Mobile communications device 280, but sensor 270 provides the reality of physical signs signal by wireless connections to mobile communications device 280 Execute example also within the scope of the invention.

In order to describe and define the purpose of the present invention, it is noted that term " substantially " be used in shown herein as can owing to appoint What Quantitative Comparison, numerical value, measured value or other intrinsic degree of uncertainty represented.Term " substantially " be also used in shown herein as In the case of the basic function without result in the present invention in discussing changes, quantificational expression can be from regulation with reference to the degree changed.

Element described herein and assembly can be further divided into add-on assemble or link together and formed identical The less assembly of function.

Can be such any with such as assembler language, machine language, high-level programming language or Object-Oriented Programming Language Programming language implements each computer program.Programming language can be compiling or interpretable programs language.

Can be at computer in being tangibly embodied in computer readable storage means, that performed by computer processor Program product is implemented each computer program.The method step of the present invention can be completed by computer processor, wherein Computer processor is performed the program that is tangibly embodied on computer-readable medium thus is inputted by operation and generate output Complete the function of the present invention.

The common form of computer-readable medium includes: such as, floppy disk, flexible disk, hard disk, tape, or other magnetic any Medium, CDROM, other optical medium any, has any physical medium of hole pattern, RAM, PROM and EPROM, FLASH- EPROM, other memory chip any or memory cartridge, all these is permanent.As United States Patent and Trademark Office 2005 is special The interim guidelines for examination 1300 communique Patent Office 142(USPTO2005Interim of lattice fitted in profit application theme Guidelines for Examination of Patent Applications for Patent Subject Matter Eligibility, 1300Off.Gaz.Pat.Office142) regulation in (on November 22nd, 2005): " on the other hand, from skill From the point of view of art angle, the signal utilizing Functional descriptive material to encode is deposited with the computer-readable utilizing Functional descriptive material to encode Reservoir is similar to, because they all produce the function mutual relation with computer.In other words, computer is able to carry out encoding merit Can, no matter whether form is disk or signal (On the other hand, from a technological standpoint,a signal encoded with functional descriptive material is similar to a computer-readable memory encoded with functional descriptive material,in that they both create a functional interrelationship with a computer.In other words,a computer is able to execute the encoded functions,regardless of Whether the format is a disk or a signal) ".

Although present invention is described to have been directed towards each embodiment, but it should be appreciated that the present invention can also exist In the spirit and scope of claim more various further and other embodiments.

Claims (36)

1. a physiological compensation effects method, it is characterised in that described method comprises:

A physical signs signal is provided to handheld mobile communications device；

Utilize handheld mobile communications device to analyze physical signs signal thus obtain the measured value of one or more physiological parameter； And

The impact of motion artifacts is also in the measured value of one or more physiological parameters to utilize the detection of handheld mobile communications device And determine whether to retain measured value；

Wherein, the impact of detection motion artifacts comprises:

Filter the fragment of the measured value from a physiological parameter and it is carried out elimination trend；Wherein through filtering and being disappeared Except hereafter the fragment of trend is referred to as pretreatment fragment；

Use the numerical value of the index of the volatibility of pretreatment fragment；And

There is not noise/motion artifacts in relatively the determining whether of the numerical value of the index according to volatibility and predetermined threshold value；

The index of wherein said volatibility comprises the comentropy of pretreatment fragment；

The step wherein detecting the impact of motion artifacts in the measurement comprises:

A. the numerical value of the index of the volatibility of pretreatment fragment is obtained；

If b. the numerical value of the index of volatibility and predetermined threshold value relatively show that noise/motion artifacts does not exists, then will This fragment is included in the analysis of physiological measure；And

If c. the numerical value of the index of volatibility can be used less than predetermined threshold value and another fragment, then select to survey from physiology Another fragment of the signal of value also forwards step (a) to.

Method the most according to claim 1, it is characterised in that the index of described volatibility also comprises kurtosis.

Method the most according to claim 1, it is characterised in that utilize experimenter's operating characteristic (ROC) to analyze and determine in advance Determine threshold value.

Method the most according to claim 1, it is characterised in that provide physical signs signal packet to contain:

The object lens of the photographing unit in described handheld mobile communications device are placed above a part for the health of main body；And

Obtain the video image of this part of the health of main body.

Method the most according to claim 1, it is characterised in that provide physical signs signal packet containing from Shellfish-based Bioelectric Sensor Obtain signal.

Method the most according to claim 5, it is characterised in that Shellfish-based Bioelectric Sensor is that light plethysmograph (PPG) passes Sensor or electrocardiography transducer.

Method the most according to claim 1, it is characterised in that one or more physiological measure comprise heart rate and heart rate becomes The opposite sex.

Method the most according to claim 7, it is characterised in that the measured value obtaining heart rate and heart rate variability comprises:

Determine beating of physical signs signal；

Determine by interval of fighting；And

Application cubic spline algorithm obtains the substantially continuous by blank signal of fighting of instruction heart rate.

Method the most according to claim 1, it is characterised in that one or more physiological measure comprise breathing rate.

Method the most according to claim 9, it is characterised in that the measured value of breathing rate comprises:

Variable frequency complex demodulation (VFCDM) is utilized to obtain the temporal frequency spectrum of physical signs signal；And

The frequency component by being extracted in each time point at heart rate frequency band with peak swing obtains breathing rate.

11. methods according to claim 1, it is characterised in that one or more physiological measure comprise oxygen saturation Measured value.

12. methods according to claim 11, it is characterised in that provide physical signs signal packet to contain:

The object lens of the photographing unit in described handheld mobile communications device are placed above a part for the health of main body；And

Obtain the video image of this part of the health of main body, and

The measured value wherein obtaining oxygen saturation comprises:

Obtain red component and the mean intensity of blue component of the video image of this part of the health of main body；Red component The mean intensity of mean intensity and blue component respectively constitutes DC_REDAnd DC_BLUE；

Obtain red component and the standard deviation of blue component；The standard deviation of red component and blue component respectively constitutes AC_RED And AC_BLUE；And

Measured value by following formula acquisition oxygen saturation (SpO2):

$SpO2=A-B\frac{{\mathrm{AC}}_{RED}/{\mathrm{DC}}_{RED}}{{\mathrm{AC}}_{BLUE}/{\mathrm{DC}}_{BLUE}}.$

13. methods according to claim 1, it is characterised in that one or more physiological measure comprise the measurement lost blood Value.

14. methods according to claim 13, it is characterised in that obtain the measured value lost blood and comprise:

Variable frequency complex demodulation (VFCDM) is utilized to obtain the temporal frequency spectrum of physical signs signal；

In the heart rate frequency band range of temporal frequency spectrum, one group of maximum instantaneous amplitude at each time sample obtains amplitude modulation (AM) sequence；And

Determine whether amplitude modulation reduces；The minimizing of amplitude modulation shows the blood loss of main body.

15. methods according to claim 1, it is characterised in that one or more physiological measure comprise atrial fibrillation Measured value.

16. methods according to claim 15, it is characterised in that the measured value obtaining atrial fibrillation comprises:

Obtain time-varying coherent function by making two time-varying transmission function (TVFT) be multiplied, utilize two proximity data fragments to obtain Two time-varying transmission functions, one of them data slot as input signal and another data slot as output, thus Produce a TVTF；The 2nd TVTF is produced by reverse input and output signal；And

Determine that whether time-varying coherent function is less than predetermined volume.

17. methods according to claim 16, it is characterised in that determine that whether time-varying coherent function is less than predetermined volume Comprise:

Obtain one or more indexs of atrial fibrillation；And

Determine whether one or more indexs of atrial fibrillation exceed predetermined threshold value.

18. methods according to claim 17, it is characterised in that one or more indexs of atrial fibrillation are covert when comprising The change of dry function.

19. methods according to claim 18, it is characterised in that one or more indexs of atrial fibrillation also comprise information Entropy.

20. methods according to claim 17, it is characterised in that utilize experimenter's operating characteristic (ROC) analysis to determine pre- First determine threshold value.

The system of 21. 1 kinds of physiological compensation effects, it is characterised in that described system comprises:

One physical signs sensing assembly；And handheld mobile communications device, wherein mobile communications device comprises:

At least one processor；At least one processor described is configured to follow the steps below:

Analyze physical signs signal thus obtain the measured value of one or more physiological parameter；And

Detection impact of motion artifacts in the measured value of one or more physiological parameters；The impact of detection motion artifacts comprises:

Filter the fragment of the measured value from a physiological parameter and it is carried out elimination trend；Wherein through filtering and being disappeared Except hereafter the fragment of trend is referred to as pretreatment fragment；

Use the numerical value of the index of the volatibility of pretreatment fragment；And

There is not noise/motion artifacts in relatively the determining whether of the numerical value of the index according to volatibility and predetermined threshold value；

The index of wherein said volatibility comprises the comentropy of pretreatment fragment；

Wherein in the impact of detection motion artifacts, at least one processor is configured to follow the steps below:

A. the numerical value of the index of the volatibility of pretreatment fragment is obtained；

If b. the numerical value of the index of volatibility and predetermined threshold value relatively show that noise/motion artifacts does not exists, then will This fragment is included in the analysis of physiological measure；

If c. the numerical value of the index of volatibility can be used, then from physiological measure less than predetermined threshold value and another fragment Select another fragment of signal and forward step (a) to.

22. systems according to claim 21, it is characterised in that the index of described volatibility also comprises kurtosis.

23. systems according to claim 21, it is characterised in that utilize experimenter's operating characteristic (ROC) analysis to determine pre- First determine threshold value.

24. systems according to claim 21, it is characterised in that physical signs sensing assembly comprises image acquisition group Part, described acquisition component can obtain a large amount of frame, obtains each frame in the predetermined time.

25. systems according to claim 24, it is characterised in that described handheld mobile communications device comprises described image Acquisition component.

26. systems according to claim 21, it is characterised in that physical signs sensing assembly comprises physiology monitoring and passes Sensor.

27. systems according to claim 26, it is characterised in that Shellfish-based Bioelectric Sensor is light plethysmograph (PPG) Sensor or electrocardiography transducer.

28. systems according to claim 21, it is characterised in that physical signs sensing assembly comprises image acquisition group Part, described acquisition component can obtain a large amount of frame, obtains each frame in the predetermined time；Wherein said image collection assembly obtains Take the coloured image with redness, green and blue component；Wherein one or more physiological measure comprise the survey of oxygen saturation Value；And wherein, in analyzing physical signs signal, at least one processor is configured to follow the steps below:

Obtain red component and the mean intensity of blue component of the image of a part for the health of main body；Red component average The mean intensity of intensity and blue component respectively constitutes DC_REDAnd DC_BLUE；

Obtain red component and the standard deviation of blue component；The standard deviation of red component and blue component respectively constitutes AC_RED And AC_BLUE；And

Measured value by following formula acquisition oxygen saturation:

$SpO2=A-B\frac{{\mathrm{AC}}_{RED}/{\mathrm{DC}}_{RED}}{{\mathrm{AC}}_{BLUE}/{\mathrm{DC}}_{BLUE}}.$

29. systems according to claim 21, it is characterised in that one or more physiological measure comprise heart rate and heart rate Variability；And wherein, in analyzing physical signs signal, at least one processor is configured to follow the steps below:

Determine beating of physical signs signal；

Determine by interval of fighting；And

Application cubic spline algorithm obtains the substantially continuous by blank signal of fighting of instruction heart rate.

30. systems according to claim 21, it is characterised in that one or more physiological measure comprise breathing rate；And And wherein, in analyzing physical signs signal, at least one processor is configured to follow the steps below:

Variable frequency complex demodulation (VFCDM) is utilized to obtain the temporal frequency spectrum of physical signs signal；And

The frequency component by being extracted in each time point at heart rate frequency band with peak swing obtains breathing rate.

31. systems according to claim 21, it is characterised in that one or more physiological measure comprise the measurement lost blood Value；And wherein, in analyzing physical signs signal, at least one processor is configured to follow the steps below:

Variable frequency complex demodulation (VFCDM) is utilized to obtain the temporal frequency spectrum of physical signs signal；

In the heart rate frequency band range of temporal frequency spectrum, one group of maximum instantaneous amplitude at each time sample obtains tune Width (AM) sequence；And

Determine whether amplitude modulation reduces；The reduction of amplitude modulation shows the blood loss of main body.

32. systems according to claim 21, it is characterised in that one or more physiological measure comprise atrial fibrillation Measured value；And wherein, in analyzing physical signs signal, at least one processor is configured to follow the steps below:

Obtain time-varying coherent function by making two time-varying transmission function (TVPT) be multiplied, utilize two proximity data fragments to obtain Two time-varying transmission functions, one of them data slot as input signal and another data slot as output, thus Produce a TVTF；The 2nd TVTF is produced by reverse input and output signal；And

Determine that whether time-varying coherent function is less than predetermined volume.

33. systems according to claim 32, it is characterised in that determining that whether time-varying coherent function is less than predetermined In amount, at least one processor is configured to follow the steps below:

Obtain one or more indexs of atrial fibrillation；And determine whether one or more indexs of atrial fibrillation exceed in advance Determine threshold value.

34. systems according to claim 33, it is characterised in that one or more indexs of atrial fibrillation are covert when comprising The change of dry function.

35. systems according to claim 34, it is characterised in that one or more indexs of atrial fibrillation also comprise information Entropy.

36. systems according to claim 34, it is characterised in that utilize experimenter's operating characteristic (ROC) analysis to determine pre- First determine threshold value.