CN109044290A - A kind of physical function check device, physical function inspection method and system - Google Patents
A kind of physical function check device, physical function inspection method and system Download PDFInfo
- Publication number
- CN109044290A CN109044290A CN201810715335.XA CN201810715335A CN109044290A CN 109044290 A CN109044290 A CN 109044290A CN 201810715335 A CN201810715335 A CN 201810715335A CN 109044290 A CN109044290 A CN 109044290A
- Authority
- CN
- China
- Prior art keywords
- signal
- sleep state
- pulse wave
- state
- wave signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000007689 inspection Methods 0.000 title claims abstract description 18
- 230000007958 sleep Effects 0.000 claims abstract description 92
- 230000036385 rapid eye movement (rem) sleep Effects 0.000 claims abstract description 48
- 210000004556 brain Anatomy 0.000 claims abstract description 47
- 238000011156 evaluation Methods 0.000 claims abstract description 31
- 230000008667 sleep stage Effects 0.000 claims abstract description 30
- 238000001514 detection method Methods 0.000 claims abstract description 24
- 238000000926 separation method Methods 0.000 claims abstract description 14
- 230000002618 waking effect Effects 0.000 claims abstract description 13
- 238000004458 analytical method Methods 0.000 claims description 35
- 230000005484 gravity Effects 0.000 claims description 32
- 238000012545 processing Methods 0.000 claims description 15
- 239000000284 extract Substances 0.000 claims description 10
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 6
- 230000000241 respiratory effect Effects 0.000 claims description 5
- 238000012854 evaluation process Methods 0.000 claims description 2
- 230000006870 function Effects 0.000 description 46
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 7
- 230000009467 reduction Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 6
- 230000010355 oscillation Effects 0.000 description 6
- 201000010099 disease Diseases 0.000 description 5
- 230000036541 health Effects 0.000 description 5
- 230000036772 blood pressure Effects 0.000 description 4
- 230000037396 body weight Effects 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 230000005059 dormancy Effects 0.000 description 4
- 238000000605 extraction Methods 0.000 description 4
- 230000006872 improvement Effects 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 210000004165 myocardium Anatomy 0.000 description 4
- 230000008452 non REM sleep Effects 0.000 description 4
- 230000033764 rhythmic process Effects 0.000 description 4
- 208000024891 symptom Diseases 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000003862 health status Effects 0.000 description 3
- 230000008035 nerve activity Effects 0.000 description 3
- 238000007639 printing Methods 0.000 description 3
- 238000001228 spectrum Methods 0.000 description 3
- 230000002889 sympathetic effect Effects 0.000 description 3
- 206010003658 Atrial Fibrillation Diseases 0.000 description 2
- 241001269238 Data Species 0.000 description 2
- 206010061216 Infarction Diseases 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000005794 circulatory dysfunction Effects 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 208000035475 disorder Diseases 0.000 description 2
- 210000001508 eye Anatomy 0.000 description 2
- 230000007574 infarction Effects 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 208000010125 myocardial infarction Diseases 0.000 description 2
- 230000004768 organ dysfunction Effects 0.000 description 2
- 230000007084 physiological dysfunction Effects 0.000 description 2
- 230000003860 sleep quality Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 206010003830 Automatism Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000003906 autonomic nervous system functioning Effects 0.000 description 1
- 210000000467 autonomic pathway Anatomy 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 210000005252 bulbus oculi Anatomy 0.000 description 1
- 230000002612 cardiopulmonary effect Effects 0.000 description 1
- 230000000739 chaotic effect Effects 0.000 description 1
- 230000027288 circadian rhythm Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- IZEKFCXSFNUWAM-UHFFFAOYSA-N dipyridamole Chemical group C=12N=C(N(CCO)CCO)N=C(N3CCCCC3)C2=NC(N(CCO)CCO)=NC=1N1CCCCC1 IZEKFCXSFNUWAM-UHFFFAOYSA-N 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000004424 eye movement Effects 0.000 description 1
- 210000000744 eyelid Anatomy 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 206010016256 fatigue Diseases 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 208000019622 heart disease Diseases 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 230000009191 jumping Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000001734 parasympathetic effect Effects 0.000 description 1
- 210000005037 parasympathetic nerve Anatomy 0.000 description 1
- 230000037081 physical activity Effects 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 230000035790 physiological processes and functions Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000004461 rapid eye movement Effects 0.000 description 1
- 230000009257 reactivity Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 210000002700 urine Anatomy 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Physics & Mathematics (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Physiology (AREA)
- Cardiology (AREA)
- Pulmonology (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The invention discloses a kind of physical function check device, physical function inspection method and system, detection units, for detecting the biological information signal of body；Signal separation unit, the biological information Signal separator for detecting the detection unit is at pulse wave signal, breath signal and body kinematics signal；Sleep state and phase judgement unit determine that the sleep state of the body and sleep stage meet one of REM sleep state, deep sleep state, sleeping state and waking state for being based on the pulse wave signal and the body kinematics signal；Causing circulatory functional evaluation unit for extracting the pulse wave signal for being in the body of the deep sleep state, and evaluates the causing circulatory function of the body；Brain control function evaluation unit for extracting the body kinematics signal for being in the body of the REM sleep state, and evaluates the brain control function of the body.
Description
Technical field
The present invention relates to a kind of physical function check device, physical function inspection method and system, in particular to a kind of use
In the physical function check device, physical function inspection method and the system that check physical function based on the biological information in sleep.
Background technique
All the time, clinical symptoms and to obtain inspection result by Medical Devices and medical image be physiological dysfunctions
Diagnostic method just applicable when symptom highly significant, before occurring for significant symptom, i.e. so-called early diagnosis it is simple,
Objective and quantitative method is not developed also so far.
Although to find out its cause, before the appearance of significant symptom, it may appear that the fluctuation of body rhythms or body pliability become
The sign of change, but it is subtle due to changing, largely by the physiology unstable state of body and the interference of external environment, institute
To be difficult to accurately capture physiological function reduction or physiological dysfunctions.
In addition, when checking physical function by measuring blood pressure or physical examination etc., preferably body is in relaxation state with can
Accurately checked.But daytime, sympathetic nerve activity was occupied an leading position, the interference that the unstability inside and outside psychosoma generates is not
It can avoid, so cannot achieve relaxation state truly.
Therefore, propose all the time it is a variety of in body it is most stable and be in relaxation state sleep when, be based on body
The physical function check device of body information inspection physical function.
For example, proposing a kind of piezoelectric transducer, health/disease severity measuring method and measurement in patent document 1
Device and measurement system (in the following, the technology is known as conventional example 1), the piezoelectric transducer is set on bedding, for detecting
Biological information in sleep；The measuring method extracts pulse wave bounce component from the original signal obtained by piezoelectric transducer
Data extract heart rate time sequence data from extracted pulse wave bounce component data, to extracted heart rate time sequence
Column data carries out near linear removing and carries out fluction analysis, measures health/disease severity by its result.
A kind of system is proposed in patent document 2, to be measured at home to sleep state, which uses sleep state
Monitoring device, the data at the bounce interval in sleep are collected by computer network, and detect the numerical value for indicating the fluctuation of bounce interval
Variation, to carry out health control to user, the sleep state monitoring device has: pressure waveform acquiring unit is used
Pressure waveform is obtained in the pressure sensing cell contacted from the body with user；Bounce extraction unit, for pressure waveform
Predetermined processing is carried out, to obtain bounce waveform；Bounce interval calculation unit, for calculating bounce interval；Sleep separation (is slept
The dormancy stage) judging unit, for being spaced the Depth of sleep stage, that is, sleep stage for determining user (in the following, by the skill by bounce
Art is known as conventional example 2).
A kind of piezoelectric transducer and system are proposed in patent document 3, the piezoelectric transducer is set on bedding, for detecting
Biological information in sleep；The system is based on the heart rate data obtained from piezoelectric transducer, thus it is speculated that meet REM sleep or
The sleep state of non rapid eye movement sleep, NREMS, while showing sleep quality (in the following, the technology is become into conventional example 3).
Patent document 1: Japanese Unexamined Patent Publication 2008-104529 bulletin
Patent document 2: Japanese Unexamined Patent Publication 2011-115188 bulletin
Patent document 3: Japanese Unexamined Patent Publication 2008-104528 bulletin.
Summary of the invention
The purpose of the present invention i.e. be to overcome the shortage of prior art, and it is an object of the present invention to provide a kind of physical function check device,
Physical function inspection method and system, the following topics exist in conventional example 1, that is, although using all data determinations in sleep
Health/disease severity of body, but due to time-bands or the difference of sleep stage, the fluctuation numerical value of body rhythms
It is uneven larger, and the fluctuation of body rhythms is ignored these unevenness and is averaged, and is determined based on this, so, numerical value is again
Existing property is poor, and precision is low.
The following topics exist in conventional example 2, that is, and it is similar with the circadian rhythm on daytime, there is also body rhythms in sleep, because
This, the figure of merit of the physical undulations of different phase can generate unevenness in sleep.And, that is, it each is slept not only for different
The dormancy stage, even if, according to the difference of the time-bands of appearance, there is also not for the numerical value of physical undulations in the identical deep sleep stage
?.For example, the physical undulations numerical value in the deep sleep stage initially occurred and the deep sleep stage finally occurred has differences.This
A little unevenness have been more than individual difference, and physical undulations are ignored these uneven differences and are averaged, and determine healthy shape based on this
State, at this point, not defining high-precision criterion.
Conventional example 3 only evaluates the sleep state of body and sleep quality, does not evaluate health status.
The present invention is to carry out in order to solve the above problems, and its purpose is to provide a kind of for based on the body in sleep
Body information is with high reproducibility and the physical function check device of high-precision inspection physical function, physical function inspection method and is
System.
The present invention is achieved through the following technical solutions:
A kind of physical function check device, comprising:
Detection unit, for detecting the biological information signal of body；
Signal separation unit, biological information Signal separator for detecting the detection unit at pulse wave signal,
Breath signal and body kinematics signal；
Sleep state and phase judgement unit determine for being based on the pulse wave signal and the body kinematics signal
The sleep state and sleep stage of the body meet REM sleep state, deep sleep state, sleeping state and awakening shape
One of state；
Causing circulatory functional evaluation unit, for extracting the pulse wave letter for being in the body of the deep sleep state
Number, and evaluate the causing circulatory function of the body；
Brain control function evaluation unit, for extracting the body fortune for being in the body of the REM sleep state
Dynamic signal, and evaluate the brain control function of the body.
Further, the detection unit is piezoelectric transducer, and the piezoelectric transducer is directly or across clothes and the body
A part contact of body.
Further, quick by being carried out to the pulse wave signal in the sleep state and phase judgement unit
Fourier transform, thus it is speculated that the supposition interval data of pulse wave signal, and using the pulse wave signal supposition interval data it
The average value and standard deviation value of data in preceding certain section calculate the Z- of the supposition interval data of pulse wave signal
Score,
The body kinematics signal speculates the body amount of movement time series data more than defined threshold, the body kinematics
The average value and standard deviation value of the data in certain section before quantity time series data use calculate body kinematics
The Z-Score of signal,
By the institute of the body kinematics signal of the Z-Score and calculating of the supposition interval data of the pulse wave signal calculated
Z-Score is stated, determines that the sleep state of the body and sleep stage meet REM sleep state, deep sleep state, shallowly sleep
One of dormancy state and waking state.
Further, in the causing circulatory functional evaluation unit, to the body for being in the deep sleep state
Pulse wave signal carry out near linear removing and carrying out fluction analysis, evaluate the causing circulatory function of the body.
Further, in the causing circulatory functional evaluation unit, the body for being in the deep sleep state is extracted
The breath signal of body calculates average respiratory cycle, carries out near linear removing to every integral multiple of the average respiratory cycle and goes forward side by side
Row fluction analysis.
Further, in the causing circulatory functional evaluation unit, to the body for being in the deep sleep state
Pulse wave signal carry out chaos analysis, the causing circulatory function of the body is evaluated based on Liapunov exponent.
Further, in the causing circulatory functional evaluation unit, the delay time being arranged in the chaos analysis is
The average period of the breath signal.
Further, in the brain control function evaluation unit, in described in the REM sleep state
The body kinematics signal of body carries out fluction analysis, and the brain control function of the body is evaluated in the shake track based on pseudo- center of gravity
Energy.
Further, in the brain control function evaluation unit, the delay time being arranged in the fluction analysis is
The average period of the breath signal.
Further, it in the causing circulatory functional evaluation unit, extracts initial in the deep sleep state
The pulse wave signal of the body for the deep sleep state that stage occurs, and evaluate the causing circulatory function of the body.
Further, it in the brain control function evaluation unit, extracts in the REM sleep state
The body kinematics signal of the body for the REM sleep state that final stage occurs, and evaluate the brain control of the body
Function processed.
Further, also there is center of gravity detection unit, for the center of gravity for detecting the body.
The present invention is realized by following another technical solutions:
A kind of physical function inspection method, comprising:
Signal separator process will be used to detect biological information detected by the detection unit of the biological information signal of body
Signal separator is at pulse wave signal, breath signal and body kinematics signal；
Sleep state and phase judgement process are based on the pulse wave signal and the body kinematics signal, described in judgement
The sleep state of body meets one of REM sleep state, deep sleep state, sleeping state and waking state；
Causing circulatory functional evaluation process extracts the pulse wave signal of the body in the deep sleep state, and
Evaluate the causing circulatory function of the body；
Brain control function evaluates process, extracts the body kinematics letter of the body in the REM sleep state
Number, and evaluate the brain control function of the body.
The present invention is realized by following yet another aspects:
A kind of physical function checks that the system system makes computer execute following processing:
Signal separation process will be used to detect biological information detected by the detection unit of the biological information signal of body
Signal separator is at pulse wave signal, breath signal and body kinematics signal；
Sleep state and phase judgement processing, are based on the pulse wave signal and the body kinematics signal, described in judgement
The sleep state of body meets one of REM sleep state, deep sleep state, sleeping state and waking state；
The pulse wave signal of the body in the deep sleep state is extracted in causing circulatory functional evaluation processing, and
Evaluate the causing circulatory function of the body；
The body kinematics letter of the body in the REM sleep state is extracted in brain control function evaluation processing
Number, and evaluate the brain control function of the body.
Compared with prior art, the present invention physical function check device, physical function inspection method according to the present invention
And system, following effect may be implemented.
(1) pulse wave signal of the body in deep sleep state is extracted, and evaluates the causing circulatory function of body, because
This, in sleep, especially in deep sleep, body is most preferably rested, and utmostly inhibits sympathetic nerve activity, parasympathetic mind
Through being in leading position, in such a state, conscious activity and internal interference are seldom, with realizing subconsciousness stable real
Relaxation state, so, can accurately check physical undulations.In addition, also passing through detection body in addition to status checkout
Fluctuation makes people find the exception of fluctuation before organic disorder, it is possible thereby to predict the exception of physical function state.
(2) the body kinematics signal of the body in REM sleep state is extracted, and evaluates the brain control function of body
Can, therefore, in stablizing sleep, brain when REM sleep is in close to waking state, controls the action of body, institute
Can detecte out brain control function obstacle and subconsciousness control by accurately checking the exception of brain control axis fluctuation
The reduction of function processed.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand the embodiment of the present invention, constitutes one of the application
Point, do not constitute the restriction to the embodiment of the present invention.In the accompanying drawings:
Fig. 1 is the block diagram for indicating the structure of the physical function check device in the first embodiment of the present invention.
Fig. 2 is for the operation and physical function inspection to the physical function check device in the first embodiment of the present invention
The flow chart that method is illustrated.
Fig. 3 is to indicate that by signal separation unit be pulse wave signal, breathing letter by the biological information Signal separator of a Dinner
Number and chart when body kinematics signal, horizontal axis be time (divide), the longitudinal axis is signal amplitude value (arbitrary unit).
In Fig. 4, (A) is the chart for showing the time series data of electrocardiogram of R-R interval, and (B) is to show the interval P-P
The chart of the time series data of pulse wave signal.
Fig. 5 is the chart indicated when selecting certain data interval W in the chart of P-P interval time sequence data.
Fig. 6 is the chart for indicating the time series variation of Z-score (dimensionless).
Fig. 7 is the chart for indicating the dormant judgement result of certain body.
In Fig. 8, (A) is to indicate Healthy People in the chart of the pulse wave signal in initial deep sleep stage, and (B) is to indicate it
The chart of breath signal, (C) are to indicate old myocardial infarction patient in the figure of the pulse wave signal in initial deep sleep stage
Table, (D) are the chart for indicating its breath signal.
Fig. 9 is the chart being illustrated for pairing approximation straight line removing-fluction analysis method.
Figure 10 be indicate by DFA calculate obtain short time region gradient slope1 and by DFA calculate obtain it is long when
Between region gradient slope2 chart, gradient slope1 is as the index of oscillation 1, and gradient slope2 is as the index of oscillation 2.
Figure 11 is for Healthy People and patient, to the 3 minutes P-P interval time sequence datas obtained by improvement DFA
Carry out that fluction analysis obtains as a result, (A) indicates the index of oscillation 1 of the two, that is, the average value of gradient slope1 value, (B) table
Show respective Distribution Value, (C) indicates the group of causing circulatory dysfunction.
In Figure 12, (A) is time series number when indicating chaos analysis for being illustrated to the summary that Ta Kensi is embedded in
According to chart, (B) be indicate in three-D state space successively draw made of track attractor chart.
Figure 13 is the explanatory diagram for indicating concept of the Liapunov exponent computational algorithm in three-dimensional state.
Figure 14 is to indicate using the Liapunov exponent computational algorithm of the circle of three radius of hypersphere under three-dimensional state
The explanatory diagram of concept.
In Figure 15, (A) is the chart of the attractor of the fluctuation degree for the Healthy People for indicating that Liapunov exponent is 4.31,
(B) be indicate Liapunov exponent be 2.55 heart muscle infarct victims fluctuation degree attractor chart.
Figure 16 is to constitute two dimension by time series data of the Ta Kensi theorem to extracted body kinematics signal to attract
The method of son illustrates chart.
In Figure 17, (A) is the time series number of extracted body kinematics signal when indicating from Healthy People REM sleep
According to chart, (B) is to indicate that its pseudo- center of gravity shakes the chart of track.
In Figure 18, (A) is extracted body kinematics signal when indicating from people's REM sleep with hot-tempered strongly fragrant tendency
The chart of time series data, (B) are to indicate that its pseudo- center of gravity shakes the chart of track.
Figure 19 indicates bed used in the physical function check device in the second embodiment of the present invention, and (A) looks up for it
Figure, (B) are its side view.
In Figure 20, (A) is the time sequence of the barycentric coodinates of body in the sleep for indicating to obtain using center of gravity detection sensor
The chart of the variation of column data, (b) center of gravity for body in expression sleep shakes the chart of track.
Label and corresponding parts title in attached drawing:
1: physical function check device
2: body
3: detection unit
4: control unit
5: storage element
6: output unit
7: communication unit
8: bed
9: signal separation unit
10: sleep state and phase judgement unit
11: causing circulatory functional evaluation unit
12: brain control function evaluation unit
13: display unit
14: printing element
15: program.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below with reference to embodiment and attached drawing, to this
Invention is described in further detail, and exemplary embodiment of the invention and its explanation for explaining only the invention, are not made
For limitation of the invention.
Fig. 1 is the block diagram for indicating the structure of the physical function check device in the first embodiment of the present invention.
(structure of the physical function check device in the first embodiment of the present invention)
As shown in Figure 1, the physical function check device 1 in the first embodiment of the present invention has: detection unit 3 is used for
Detect the biological information signal of body 2；Control unit 4, for being carried out to the biological information signal detected by detection unit 3
Signal processing determines sleep state and sleep stage (sleep stage), evaluates physical function；Storage element 5；Output unit 6；
Communication unit 7.
Detection unit 3 is to use directly or across the piezoelectric transducer that clothes is contacted with a part of body 2 for example, being set to
In on the bed 8 that body 2 is slept.
Control unit 4 has: signal separation unit 9, for will test biological information Signal separator detected by unit 3
At pulse wave signal, breath signal and body kinematics signal；Sleep state and phase judgement unit 10, for being based on pulse wave
Signal and body kinematics signal determine that the sleep state of body 2 and sleep stage meet REM sleep state, deep sleep shape
It is any in state, sleeping state and waking state；Causing circulatory functional evaluation unit 11 is in deep sleep for extracting
The pulse wave signal of the body 2 of state, and evaluate the causing circulatory function of body 2；Brain control function evaluation unit 12 is used
In the body kinematics signal of body 2 of the extraction in REM sleep state, and evaluate the brain control function of body 2.
Storage element 5 stores various data, has database etc..
Output unit 6 exports various data, has the display units 13 such as display screen, display, for showing various data；
And the printing elements such as printer 14, for printing various data.
Communication unit 7 carries out sending and receiving for various data, (to be based on TCP/IP (Transmission with internet
Control Protocol/Internet Protocol) data transmission network) and LAN (Local Area Network) etc.
Communication network connection, for example, being modem, terminal adapter, router, DSU (Digital Service Unit)
Deng.
In addition, the control for the physical function check device for executing computer in the first embodiment of the present invention by program 15
The control of unit 4 is handled.The program 15 can recorde in the record medias such as disk, CD-ROM, semiconductor memory, can also
With from downloaded.
(operation and physical function inspection method of the physical function check device in the first embodiment of the present invention) Fig. 2 is
For to the physical function check device in the first embodiment of the present invention operation and physical function inspection method be illustrated
Flow chart.
Firstly, detecting biological information signal (step S1) by detection unit 3.
Then, biological information signal detected by unit 3 point will test by the signal separation unit 9 of control unit 4
From at pulse wave signal, breath signal and body kinematics signal (step S2).
Then, by sleep state and phase judgement unit 10, it is based on pulse wave signal and body kinematics signal, determines body
The sleep state of body 2 meets any (step in REM sleep state, deep sleep state, sleeping state and waking state
Rapid S3).
Then, the pulse wave signal (step S4) for extracting the body 2 in deep sleep state, is commented by causing circulatory function
The causing circulatory function (step S5) of the evaluation body 2 of valence unit 11.
In addition, extracting the body kinematics signal (step S6) of the body 2 in REM sleep state, controlled by brain
The brain control function (step S7) of the evaluation body 2 of functional evaluation unit 12.
In the following, the processing carried out using control unit 4 is described in detail.
(processing of step S2)
Fig. 3 is to indicate that the information signal of one Dinner of body is separated into pulse wave signal, breathing letter by signal separation unit
Number and body kinematics signal chart, horizontal axis be time (divide), the longitudinal axis for signal amplitude.In figure, lower part indicates pulse wave
Signal, middle part indicate breath signal, and top indicates body kinematics signal.
As shown in figure 3, biological information signal is divided into pulse wave signal (centre frequency 1Hz), breath signal (center frequency
Rate 0.3Hz) and body kinematics signal (2Hz) respective centre frequency around frequency band, be separated into three signals.
(processing of step S3)
Since the brain of people is very flourishing, REM sleep and non rapid eye movement sleep, NREMS are differentiated, undertakes difference respectively
Effect.REM sleep rolls under the eyelid closed from eyeball and rotates i.e. rapid eye movement (rapid eye
The initial of movement is REM) this word.Brain when REM sleep is in the state close to awakening, in the state
Under, often have a dream, although body is very tired out in a dormant state.The Autonomic nervous system functions such as pulse, breathing, blood pressure are not advised
Then change, therefore body activity in a manner of when being different from awakening.
Non rapid eye movement sleep, NREMS refers to the suspend mode of non rapid eye movement sleep, NREMS, that is, includes that shallow dormancy state to state of sleeping soundly completely (is based on
Brain wave is divided into four-stage) stable suspend mode.Body muscle keeps relatively nervous, the self-discipline mind such as pulse, breathing, blood pressure
Through function-stable.
Now, the sleep state determination method for medically approving and obtaining clinical application is polysomnogram
(Polysomnography:PSG) method.Polysomnogram method is to measure brain wave, eye movement and mentalis electricity and by them
The method that waveform is determined.But in the method for measurement brain wave, myoelectricity etc., need that electrode is physically installed, this
It is very big burden for subject, general family can not be measured.Therefore, present invention employs a kind of substitution is more
It leads hypnogram and dormant method is speculated by easy method.
(1) interval P-P PPI is speculated by pulse wave signal
The P-P interval time sequence data for the R-R interval being equivalent in electrocardiogram is speculated by pulse wave signal.
In Fig. 4, (A) is the chart for showing the time series data of electrocardiogram of R-R interval, and (B) is to show the interval P-P
The chart of the time series data of pulse wave signal.Here, R-R interval is the interval of the R wave of electrocardiogram, pulse is divided between P-P
Wave signal it is peak-to-peak every.
Firstly, in order to measure the peak of pulse wave and peak-to-peak every using Fast Fourier Transform (FFT).To pulse wave signal
Data carry out fft analysis, calculate average frequency (MPF) and power (P).
MPF refers to the average value of the frequency spectrum of each frequency.Formula is as follows.
Wherein, P is the performance number of power spectrum, and f is frequency, and fl and fh are the low frequency value and height for indicating frequency analysis section
Frequency values.Using these, pass through the following interval data PPI for obtaining formula (2) and acquiring pulse wave signal.
PPI=1/MPF formula (2)
(2) speculate the Z-score of PPI
Fig. 5 is the chart indicated when selecting certain data interval W in the chart of the time series data of PPI.
For PPI time series data, when using certain data interval W before PPI value, the data in the W of section are used
Average value Mean and standard deviation S D, pass through formula (3) calculate PPI Z-score.
Z-score=(PPI value-Mean)/SD
Formula (3)
By sliding data interval W, the Z-score time series data of PPI is generated.
Fig. 6 is the chart for indicating the variation of time series of Z-score (dimensionless).
As shown in fig. 6, Z-Score absorbs respective individual difference by average and standard deviation, in substantially ± 3 ranges
Numerical value (dimensionless) general appropriate threshold value (numerical value) therefore can be set.
(3) speculate the Z-score of body kinematics
Body kinematics signal calculates the body kinematics quantity for exceeding defined threshold, the body kinematics quantity time series data
The average value Mean and standard deviation value SD of the data of certain section W before use, thus it is speculated that the body obtained according to formula (2)
The Z-Score of body movement signal.By sliding data interval W, the Z-score time series data of body kinematics signal is generated.
(4) determine sleep stage (awakening, deep sleep, shallow sleep, REM sleep)
Under deep sleep state, the Z-Score of heart rate fluctuations, that is, pulse wave signal interval data PPI is minimum, meanwhile, body
Body movement is also smaller, i.e., the Z-Score of body kinematics is minimum.
In contrast, above-mentioned both maximum under waking state.
Shallow sleep, REM sleep are located between the two.
Therefore, the threshold value of the Z-Score of PPI is such as set as PT1, PT2, PT3, the threshold of the Z-Score of body kinematics signal
Value is set as MT1, MT2, MT3, then
As Z-Score < PT1 of PPI, meanwhile, when Z-Score < T1 of body kinematics, it is determined as the deep sleep stage.
As PT2 > Z-Score > PT1 of PPI, meanwhile, when MT2 > body kinematics Z-Score > MT1 of body kinematics, determine
For shallow sleep stage.
As PT3 > Z-Score > PT2 of PPI, meanwhile, when MT3 > body kinematics Z-Score > MT2 of body kinematics, determine
For the REM sleep stage.
As Z-Score > PT3 of PPI, meanwhile, when body kinematics Z-Score > MT3 of body kinematics, it is judged to awakening.
Wherein, PT1 < PT2 < PT3, MT1 < MT2 < MT3.Thus, it is possible to determine that sleep state is in any sleep stage
Or any sleep stage.
The specific threshold value of the present inventor's actual use is as follows:
PT1=0.6, PT2=1.2, PT3=3；
MT1=0.7, MT2=1, MT3=3
(these are merely illustrative, are not limited to this).
Fig. 7 is the chart for indicating the dormant judgement result of certain body.
(processing of step S4 and S5)
(1) signal extraction in deep sleep stage
Divided band, pulse wave signal (centre frequency 1Hz) and breath signal (centre frequency after extracting separation
0.3Hz).By above-mentioned means, dormant judgement result as shown in Figure 7 is obtained.Multiple deep sleep stages are obtained,
The deep sleep stage indicated by an arrow initially occurred is most stable of real relaxation state.In addition, obtaining multiple fast
Dynamic eye sleep stage, the REM sleep stage indicated by an arrow occurred at first, for the sleep state of closest awakening.
In Fig. 8, (A) is the chart for indicating the pulse wave signal extracted from the initial deep sleep stage of Healthy People, and (B) is table
Show the chart of its breath signal, (C) is the pulse wave for indicating to extract from the initial deep sleep stage of old myocardial infarction patient
The chart of signal, (D) are the chart for indicating its breath signal.
(2) heart claps the analysis method (improvement DFA method) of fluctuation
One of fractals method, that is, near linear removing-wave is carried out to heart rate data according to newest research results
Dynamic analysis, that is, the DFA (Detrended Fluctuation Analysis) taken into account that influences each other of cardiopulmonary is analyzed,
Thus, thus it is speculated that the physical function of heart disease and Other diseases and causing circulatory reduces or obstacle.
From pulse wave, interval PPI time series data is set as X (1), X (2), X (3), K, X (N).
Firstly, calculating whole average value.Average value is subtracted from each value of time series data and it is integrated in the hope of y
(k).According to formula (4), time series data is the discrete data at each moment, thus integral be replaced into and.
Fig. 9 is the chart being illustrated for pairing approximation straight line removing-fluction analysis method.
Wherein, X (i): time series data [i=1, K, N], M:X's (i) is averaged.
Then, the time series y (k) after time segmentation integrates is distinguished with n at equal intervals, is acquired most within the differentiation time
Small square near linear yn(k) (local trend).From removing y in y (k)n(k) trend and squared acquirement average value obtain
Square root, F (n) (mean square error) at this time are formula (5).Make the relatively whole markers variations of the size for distinguishing the time, for each
Time calculating F (n) is distinguished, horizontal axis plot distinguishes the logarithm log n of time, indulges axis plot mean square error average value F (n)
Logarithm log F (n).
Figure 10 be indicate by DFA calculate obtain short time region gradient slope1 and by DFA calculate obtain it is long when
Between region gradient slope2 chart, gradient slope1 is as the index of oscillation 1, and gradient slope2 is as the index of oscillation 2.
In the point range figure of logn shown in Fig. 10 and logF (n), the gradient of straight line portion is scaled index Slope1.It is logical
The straight line gradient that least squares method acquires is crossed to be corresponding to it.
The present invention will breathe the fluction analysis precision for the pulse wave spacing PPI that the influence generated is taken into account to improve,
And use the raising precision methods of DFA method.Wherein, using the Tr for being equivalent to average respiratory cycle.
When the n in formula (5) selectes the integral multiple of Tr: when n=Tr, 2Tr, 3Tr, 4Tr ..., when each differentiation of formula (5)
Between F (n) jump at the integral multiple of each respiratory cycle, reduce breathing to PPI fluctuation generate influence, thus obtain just
True PPI index of oscillation Slope1.
By the Slope1, classified as follows to PPI time series data X (i).
0 < Slope1 < 0.5: inverse correlation
Slope1=0.5: irrelevant, white noise
0.5 < Slope1 < 1.0: long-range is related
Slope1=1:1/f fluctuation
Linear relation collapse between Slope1 > 1:logn and logF (n)
Slope1=1.5: walk random type brown noise
Figure 11 is using the 3 minutes P-P interval time sequence datas obtained by improvement DFA to healthy population and following
Ring organ dysfunction reduce crowd carry out fluction analysis and obtain as a result, (A) indicate both Slope1 value average value and mark
Quasi- error, (B) indicate respective Distribution Value, and (C) is the group for showing Healthy People and causing circulatory function reduction person.
By the analysis it is found that when body is in health status, Slope1 value is recycled close to 1 (1/f fluctuation), atrial fibrillation etc.
Organ dysfunction reduces crowd close to 0.5.Crowds Distribute is reduced near 0.9 with hypertension or anginal function, with sugar
The function of urine disease or heart muscle infraction reduces Crowds Distribute near 0.6~0.7, and the function with atrial fibrillation reduces crowd point
Cloth is near 0.5.
That is, indicating that 1/f is fluctuated under health status with Slope1=1, as causing circulatory function reduces adding for degree
Weight, Slope1 are gradually reduced, it is considered that close to irrelevant, white noise i.e. 0.5.That is, it is considered that such as due to autonomic nerve
The fluctuation (variation) generated to the domination of pacemaker reduces, then for being applied to the quick compensation sharply interfered of blood pressure
Property and reactivity reduce, so as to cause causing circulatory function reduction.
In addition, being then thought of as the unsound state of psychology as Slope1 value rises to 1 or more.If undue fluctuation, for pressure
Power state or the psychological condition felt out of one's plate.
(3) chaos analysis of pulse wave signal
Figure 12 (A) is the chart for indicating the time series data being illustrated for the summary to Ta Kensi embedding theorems,
(B) the attractor chart to indicate track made of successively drawing in three-D state space.
Ta Kensi theorem is the method generally used in chaos analysis.The time series data of pulse wave signal is set as x
(k) (k=0,1,2,3 ...).
When wanting to restore the attractor of m state variable, using delay time T, vector x (i)={ x (i), x (i+ is made
τ),x(i+2τ),……x(i+mτ)}.For example, when the number of state variable is 3, x (i)={ x (i), x (i+ τ), x (i+
2τ)}。
τ herein is parameter, referred to as insertion delay time.Such as in three-dimensional state space (reference axis x (i), x (i+ τ) and
X (i+2 τ)) successively draw the vector x (i) (i=0,1,2 ..., n), then track can be obtained, the shape of the track is referred to as
Attractor.
Delay time T selection is most important, can restore the attractor of state variable by selection Best Times delay.This
Invention uses optimum delay time τ=pulse wave signal average period.Thus, it is possible to restore attractor, so that pulse wave is believed
Number the precision of chaos analysis result be improved.
Liapunov exponent is the index for indicating signal fluctuation degree, is drawn in track in attractor, close to two rails
Distance between road is to indicate to pass through at any time and the amount of separate degree.When calculating Liapunov exponent, basis is used
The approximate calculation method of Sano-Sawada method.
Figure 13 is the explanatory diagram for indicating concept of the Liapunov exponent computational algorithm under three-dimensional state.
As shown in figure 13, when being used as initial value to the microballoon (hypersphere) that three-dimensional chaos dynamics system provides radius ε, it is initially
The substance of sphere is pulled up in the side e1, flattens on the direction e3 after once mapping, and as a result forms ellipse.If will at this time
Logarithm relative to the unit time amplification degree on the direction e1, e2, e3 is set as λ 1, λ 2, λ 3, then the λ 1 is the first component, therefore
Also referred to as " the first Liapunov exponent ", " largest Lyapunov exponent " are denoted as Liapunov exponent in the present invention
(non-patent literature M.Sano, Y.Sawada (1985) Measurement of the Lyapunov spectrum from a
chaotic time series,Physical Review Letters,55(10)pp1082-1085)。
In the present invention, in order to remove the surrounding enviroment noise being mixed into signal, following method is designed, to improve essence
Degree.
Figure 14 is to indicate general under three-dimensional state using the Liapunov exponent computational algorithm of three radius of hypersphere circle
The explanatory diagram of thought.
As shown in figure 14, another radius of hypersphere ε 3 is added, that is, as the search condition of attractor neighbor point,
It will be present in radius of hypersphere ε 1, and,
It is present in radius of hypersphere ε 2, and,
It is present in the point of the attractor in radius of hypersphere ε 3 as neighbor point.
Wherein, radius of hypersphere 1 uses the 5% of attractor overall dimension (radius),
When setting radius of hypersphere 2 is 1.5 times of radius of hypersphere 1,
When radius of hypersphere 3 is 2 times of radius of hypersphere 1,
It can inhibit noise, improve precision.
To find out its cause,
1) track for jumping out hypersphere ε 2 and hypersphere ε 3 can be detached from.
2) track (noise) of different behaviors can be detached from and calculate Liapunov exponent.
In Figure 15, (A) is the attractor chart of the fluctuation degree for the Healthy People for indicating that Liapunov exponent is 4.31, (B)
For indicate Liapunov exponent be 2.55 heart muscle infarct victims fluctuation degree attractor chart.
Liapunov exponent indicate body pliability and physical undulations degree, Healthy People even at rest state still
Liapunov exponent with higher, extremely flexibly changes, moreover, showing complicated attraction minor structure in Figure 15 (A)
Chart.
On the other hand, if gradually losing flexible mobility, Liapunov exponent reduces, and physical function reduces, and produces
The risk of the causing circulatory dysfunctions such as raw heart muscle infraction is larger, at this point, showing the simple week after reducing in Figure 15 (B)
Phase property attracts minor structure.
(processing of step S6 and S7)
The last REM sleep stage closest to waking state, in this state, most preferably can check body from brain
Therefore the movable control function of body by analyzing body kinematics fluctuation at this time, can accurately check brain
Control function.As its method, in an evening, the signal in last REM sleep stage is extracted, by carrying out to body movement
Fluction analysis checks that potential body relevant to brain control function is unbalance, so as to predict mental handicape.
(1) signal extraction in REM sleep stage
Body kinematics signal is extracted from the REM sleep stage for being judged to finally occurring in sleep stage.
(2) fluction analysis of body kinematics signal
The fluction analysis of body kinematics signal uses and the center of gravity method that shake inspection similar.
Figure 16 is the time series data for extracted body kinematics signal, two-dimentional to constituting by Ta Kensi theorem
The chart that the point of attractor is illustrated.Figure 17 is that obtained two-dimentional attractor is shown as the figure that pseudo- center of gravity shakes track as a result,
Table.
As shown in figure 16, by Ta Kensi theorem, body kinematics signal when by extracted REM sleep constitutes two
Tie up attractor.As shown in figure 17, shake track for the attractor as pseudo- center of gravity, shake inspection using centre of body weight when standing
Checking method.
The present invention uses optimum delay time τ=breath signal average period, can reduce the influence of breathing, Neng Goujing
Really constitute two-dimentional attractor.
In Figure 17, (A) is the time for indicating the body kinematics signal extracted from the Healthy People last REM sleep stage
The chart of sequence data, (B) are to indicate that its pseudo- center of gravity shakes the chart of track.
In Figure 18, (A) is to indicate from the last REM sleep stage of the people with hot-tempered strongly fragrant tendency extracted body fortune
The chart of the time series data of dynamic signal, (B) are to indicate that its pseudo- center of gravity shakes the chart of track.
As shown in figure 17 it is found that pseudo- center of gravity, which can be well controllled, in the people of physical function health shakes track, track area
It is smaller, in contrast, as shown in figure 18 it is found that with hot-tempered strongly fragrant tendency or unsound people, brain control function reduce,
Cause track area larger.
(second embodiment)
Figure 19 indicates bed used in the physical function check device in the second embodiment of the present invention, and (A) looks up for it
Figure, (B) are its side view.
As shown in figure 19, in the physical function check device of the second embodiment of the present invention, what is slept for body 2
The lower part of the leg 8a of bed 8 is equipped with the center of gravity detection sensor 21 (weight sensor) of the center of gravity for detecting body 2.
The length of bed 8 and width are set as L and D.Origin (0,0) of the central point as the plane coordinates (x, y) of center of gravity.
By the weight sensor on 4 leg 8a of bed 8, weight value P1, P2, P3, P4 of 4 legs are measured, by
This,
In sleep, the x coordinate value of centre of body weight=[(P1+P2) * L/2- (P3+P4) * L/2]/Pt on bed short-axis direction；
In sleep, the y-coordinate value of the center of gravity of body=[(P1+P3) * D/2- (P2+P4) * D/2]/Pt on bed long axis direction；
Wherein, total weight Pt=P1+P2+P3+P4,
The time-variable data of the y-coordinate value of the x coordinate value and center of gravity of center of gravity is as biological information signal.
By the filtering method of Signal separator, according to respective band separation at three body signals.That is, pulse wave signal
(centre frequency 1Hz), breath signal (centre frequency 0.3Hz), body kinematics signal (centre frequency 2Hz).Utilize these separation
Signal determines sleep stage by Z-Score method.It is same as Example 1, by deep sleep stage and REM sleep
The signal in stage carries out fluction analysis and chaos analysis, can check physical function reduction.
Moreover, the centre of body weight occurred under flat-hand position is known as the horizontal center of gravity of two-dimensional projection in the sleep of body 2,
The figure that its barycenter trajectory is changed over time as the x coordinate value and y-coordinate value of center of gravity.
The figure of the y-coordinate value of the x coordinate value and center of gravity of the center of gravity at each moment is inhaled with the two dimension being made of barycenter trajectory
Introduction is identical, and therefore, being calculated by formula (6) can be around track that the counterweight control function aroused in interest shaken is evaluated
Outer circumferential area evaluation index.
Outer circumferential area Env.Area:
Env.Area=(max (x)-min (x)) * (max (y)-min (y)) formula (6)
The scope of activities of center of gravity is the rectangle as all surrounding.
The areal analysis of track can be shaken by center of gravity, detect the reduction of brain control function.
In Figure 20, (A) is the figure for indicating the variation of time series data of the barycentric coodinates obtained using weight sensor
Table, (B) are indicated using centre of body weight as the chart of shake track when the horizontal center of gravity of two-dimensional projection.
This method can be not only used for pseudo- center of gravity and shake, and actually can be used in sleep from the center of gravity for being installed on bed 8
The trajectory analysis for the body levels center of gravity that detection sensor 21 obtains, moreover, it is also possible to as detection body control or greatly
The means that brain control function reduces.
Physical function check device and system according to the present invention, may be implemented following effect.
(1) pulse wave signal of the body in deep sleep state is extracted, and evaluates the causing circulatory function of body, because
This, in sleep, especially in deep sleep, body is in most stable of relaxation state, utmostly inhibit sympathetic nerve activity,
Parasympathetic nerve is in leading position, and in such a state, conscious activity and internal interference are seldom, realizes under subconsciousness
Real relaxation state, so, it is uneven less, it can accurately check fluctuation.In addition, also passing through in addition to status checkout
It checks physical undulations, people is made to find the exception of fluctuation before organic disorder, it is possible thereby to which prediction loop function reduces.
(2) the body kinematics signal for being in REM sleep state is extracted, and evaluates body control or brain control
Therefore function is stablized in sleep, brain when REM sleep is in the state close to awakening, by accurately checking control
The function of body movement can detect brain control function obstacle or subconsciousness control function in sleep under automatism
The reduction of energy.
The present invention is not limited to the above embodiments, as each in the range of the technology item that can be recorded in the claims
Kind change.
Above-described specific embodiment has carried out further the purpose of the present invention, technical scheme and beneficial effects
It is described in detail, it should be understood that being not used to limit this hair the foregoing is merely a specific embodiment of the invention
Bright protection scope, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should all
It is included within protection scope of the present invention.
Claims (14)
1. a kind of physical function check device characterized by comprising
Detection unit, for detecting the biological information signal of body；
Signal separation unit, the biological information Signal separator for detecting the detection unit is at pulse wave signal, breathing
Signal and body kinematics signal；
Sleep state and phase judgement unit, for being based on the pulse wave signal and the body kinematics signal, described in judgement
The sleep state and sleep stage of body meet in REM sleep state, deep sleep state, sleeping state and waking state
One kind；
Causing circulatory functional evaluation unit, for extracting the pulse wave signal for being in the body of the deep sleep state, and
Evaluate the causing circulatory function of the body；
Brain control function evaluation unit, for extracting the body kinematics letter for being in the body of the REM sleep state
Number, and evaluate the brain control function of the body.
2. physical function check device according to claim 1, which is characterized in that the detection unit is piezoelectric sensing
Device, the piezoelectric transducer is direct or contacts across clothes with a part of the body.
3. physical function check device according to claim 2, which is characterized in that in the sleep state and phase judgement
In unit, by carrying out Fast Fourier Transform to the pulse wave signal, thus it is speculated that the supposition interval data of pulse wave signal, and
Use the average value and standard deviation value of the data in certain section before the supposition interval data of the pulse wave signal, meter
The Z-Score of the supposition interval data of pulse wave signal is calculated,
The body kinematics signal speculates the body amount of movement time series data more than defined threshold, the body kinematics quantity
The average value and standard deviation value of the data in certain section before time series data use calculate body kinematics signal
Z-Score,
By the Z- of the body kinematics signal of the Z-Score and calculating of the supposition interval data of the pulse wave signal calculated
Score determines that the sleep state of the body and sleep stage meet REM sleep state, deep sleep state, shape of shallowly sleeping
One of state and waking state.
4. physical function check device according to claim 3, which is characterized in that in the causing circulatory functional evaluation list
In member, near linear removing is carried out to the pulse wave signal of the body in the deep sleep state and is gone forward side by side dynamic point of traveling wave
Analysis, evaluates the causing circulatory function of the body.
5. physical function check device according to claim 4, which is characterized in that in the causing circulatory functional evaluation list
In member, the breath signal of the body in the deep sleep state is extracted, average respiratory cycle is calculated, to the average breathing
Every integral multiple in period carries out near linear removing and carries out fluction analysis.
6. physical function check device according to any one of claims 1-5, which is characterized in that in the causing circulatory
In functional evaluation unit, chaos analysis is carried out to the pulse wave signal of the body in the deep sleep state, is based on Lee
The causing circulatory function of body described in Ya Punuofu index assessment.
7. physical function check device according to claim 6, which is characterized in that in the causing circulatory functional evaluation list
In member, the delay time being arranged in the chaos analysis is the average period of the breath signal.
8. physical function check device according to claim 7, which is characterized in that evaluated in the brain control function single
In member, fluction analysis is carried out to the body kinematics signal of the body in the REM sleep state, based on pseudo- center of gravity
Shake track evaluate the brain control function of the body.
9. physical function check device according to claim 8, which is characterized in that evaluated in the brain control function single
In member, the delay time being arranged in the fluction analysis is the average period of the breath signal.
10. physical function check device according to claim 9, which is characterized in that in the causing circulatory functional evaluation
In unit, the pulse wave letter of the body for the deep sleep state that the initial period in the deep sleep state occurs is extracted
Number, and evaluate the causing circulatory function of the body.
11. physical function check device according to claim 10, which is characterized in that evaluated in the brain control function
In unit, the body for the REM sleep state that the final stage in the REM sleep state occurs is extracted
Body kinematics signal, and evaluate the brain control function of the body.
12. physical function check device according to claim 11, which is characterized in that further have center of gravity detection single
Member, for the center of gravity for detecting the body.
13. a kind of physical function inspection method characterized by comprising
Signal separator process will be used to detect biological information signal detected by the detection unit of the biological information signal of body
It is separated into pulse wave signal, breath signal and body kinematics signal；
Sleep state and phase judgement process are based on the pulse wave signal and the body kinematics signal, determine the body
Sleep state meet one of REM sleep state, deep sleep state, sleeping state and waking state；
Causing circulatory functional evaluation process, extracts the pulse wave signal of the body in the deep sleep state, and evaluates
The causing circulatory function of the body；
Brain control function evaluates process, extracts the body kinematics signal of the body in the REM sleep state,
And evaluate the brain control function of the body.
14. a kind of physical function checks system, which is characterized in that the system makes computer execute following processing:
Signal separation process will be used to detect biological information signal detected by the detection unit of the biological information signal of body
It is separated into pulse wave signal, breath signal and body kinematics signal；
Sleep state and phase judgement processing, are based on the pulse wave signal and the body kinematics signal, determine the body
Sleep state meet one of REM sleep state, deep sleep state, sleeping state and waking state；
Causing circulatory functional evaluation processing, extracts the pulse wave signal of the body in the deep sleep state, and evaluates
The causing circulatory function of the body；
Brain control function evaluation processing, extracts the body kinematics signal of the body in the REM sleep state,
And evaluate the brain control function of the body.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810715335.XA CN109044290A (en) | 2018-06-29 | 2018-06-29 | A kind of physical function check device, physical function inspection method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810715335.XA CN109044290A (en) | 2018-06-29 | 2018-06-29 | A kind of physical function check device, physical function inspection method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109044290A true CN109044290A (en) | 2018-12-21 |
Family
ID=64819024
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810715335.XA Pending CN109044290A (en) | 2018-06-29 | 2018-06-29 | A kind of physical function check device, physical function inspection method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109044290A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020224026A1 (en) * | 2019-05-09 | 2020-11-12 | 深圳六合六医疗器械有限公司 | Dynamic monitoring method for deep sleep |
| CN112370013A (en) * | 2020-07-31 | 2021-02-19 | 新绎健康科技有限公司 | Method and system for determining sleep stage |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008104528A (en) * | 2006-10-23 | 2008-05-08 | Rokko Bussan:Kk | Sleep evaluating method, sleep evaluating apparatus, and sleep evaluating system |
| WO2011046178A1 (en) * | 2009-10-14 | 2011-04-21 | 株式会社デルタツーリング | Biological state estimation device, biological state estimation system, and computer program |
| JP2011115188A (en) * | 2008-06-13 | 2011-06-16 | Heart Metrics Kk | Sleeping condition monitoring apparatus, monitoring system, and computer program |
| CN103263261A (en) * | 2013-05-02 | 2013-08-28 | 北京博实联创科技有限公司 | System for presuming sleep indexes and sleep stages by method for measuring physiological parameters in unconstrained manner |
| CN104382574A (en) * | 2014-11-06 | 2015-03-04 | 李久朝 | Method and system for monitoring sleep quality based on pulse wave data |
| JP2017063997A (en) * | 2015-09-29 | 2017-04-06 | 株式会社Ｔａｏｓ研究所 | Biological function examination device, biological function examination method and program |
| CN210446992U (en) * | 2018-06-29 | 2020-05-05 | 苗铁军 | Physical function examination device |
-
2018
- 2018-06-29 CN CN201810715335.XA patent/CN109044290A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008104528A (en) * | 2006-10-23 | 2008-05-08 | Rokko Bussan:Kk | Sleep evaluating method, sleep evaluating apparatus, and sleep evaluating system |
| JP2011115188A (en) * | 2008-06-13 | 2011-06-16 | Heart Metrics Kk | Sleeping condition monitoring apparatus, monitoring system, and computer program |
| WO2011046178A1 (en) * | 2009-10-14 | 2011-04-21 | 株式会社デルタツーリング | Biological state estimation device, biological state estimation system, and computer program |
| CN103263261A (en) * | 2013-05-02 | 2013-08-28 | 北京博实联创科技有限公司 | System for presuming sleep indexes and sleep stages by method for measuring physiological parameters in unconstrained manner |
| CN104382574A (en) * | 2014-11-06 | 2015-03-04 | 李久朝 | Method and system for monitoring sleep quality based on pulse wave data |
| JP2017063997A (en) * | 2015-09-29 | 2017-04-06 | 株式会社Ｔａｏｓ研究所 | Biological function examination device, biological function examination method and program |
| CN210446992U (en) * | 2018-06-29 | 2020-05-05 | 苗铁军 | Physical function examination device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020224026A1 (en) * | 2019-05-09 | 2020-11-12 | 深圳六合六医疗器械有限公司 | Dynamic monitoring method for deep sleep |
| CN112370013A (en) * | 2020-07-31 | 2021-02-19 | 新绎健康科技有限公司 | Method and system for determining sleep stage |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6356616B2 (en) | Sequential posture identification device, autonomic nerve function information acquisition device, method and program | |
| Paalasmaa et al. | Adaptive heartbeat modeling for beat-to-beat heart rate measurement in ballistocardiograms | |
| EP3454743B1 (en) | Determination system and method for determining a sleep stage of a subject | |
| JP6627112B2 (en) | Biological function testing device, method of operating biological function testing device, and program | |
| EP2498676A1 (en) | Brain activity as a marker of disease | |
| Tataraidze et al. | Bioradiolocation-based sleep stage classification | |
| JP5776939B2 (en) | Sleep state determination device and sleep state determination method | |
| EP3897355B1 (en) | System and method for detecting fluid accumulation | |
| Alivar et al. | Motion detection in bed-based ballistocardiogram to quantify sleep quality | |
| CN109219387A (en) | For assessing the cardiodynamics cross-spectral density of sleep physiology | |
| González et al. | Poincaré plot analysis of cerebral blood flow signals: Feature extraction and classification methods for apnea detection | |
| JP2018082931A (en) | Arousal level processing method and arousal level processing apparatus | |
| CN109044290A (en) | A kind of physical function check device, physical function inspection method and system | |
| JP6291922B2 (en) | Sleep depth determination device | |
| Tiwari et al. | Stress and anxiety measurement" in-the-wild" using quality-aware multi-scale hrv features | |
| Geman et al. | Using wavelet for early detection of pathological tremor | |
| Paalasmaa | Monitoring sleep with force sensor measurement | |
| Tataraidze et al. | Sleep stage classification based on bioradiolocation signals | |
| Kinoshita et al. | Polysomnography | |
| CN210446992U (en) | Physical function examination device | |
| JP2010012100A (en) | Sleepiness detector | |
| Tao et al. | Activity selection to distinguish healthy people from parkinson’s disease patients using i-da | |
| KR101530494B1 (en) | Device and method for discriminant model to determine sex addict using standardized sexual arousal and functional magnetic resonance imaging | |
| Lee et al. | Monitoring obstructive sleep apnea with electrocardiography and 3-axis acceleration sensor | |
| Ku et al. | Novel Biometrics: Analysis of an Unattended Health Monitoring System |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181221 |