CN108175382A - Contactless sleep evaluation method and device based on CPC - Google Patents
Contactless sleep evaluation method and device based on CPC Download PDFInfo
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- CN108175382A CN108175382A CN201810024192.8A CN201810024192A CN108175382A CN 108175382 A CN108175382 A CN 108175382A CN 201810024192 A CN201810024192 A CN 201810024192A CN 108175382 A CN108175382 A CN 108175382A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4818—Sleep apnoea
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—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
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/0816—Measuring devices for examining respiratory frequency
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—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
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6892—Mats
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7475—User input or interface means, e.g. keyboard, pointing device, joystick
Abstract
A kind of contactless sleep evaluation method and device based on CPC provided in an embodiment of the present invention.Wherein, the method generates fine motion data by receiving according to human organ microvibration signal.Multiresolution wavelet conversion process is carried out to fine motion data, to obtain heart rate monitor reference number and respiratory rate characterization signal, and extracts corresponding heart rate sequence and respiratory rate sequence from heart rate monitor reference number and respiratory rate characterization signal respectively.Corresponding coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure are generated according to heart rate sequence and respiratory rate sequence, carry out sleep evaluation.The physical sign parameters of multiple types need not be acquired, reduce the dimension and difficulty of data acquisition, also reduce the cost of equipment, convenient for promoting.Simultaneously as multiresolution wavelet conversion process is carried out using the fine motion data to organ, to isolate heart rate monitor reference number and respiratory rate characterization signal；It is therefore not necessary to which fine motion sensing device is contacted with body surface, avoid influencing subject.
Description
Technical field
The present invention relates to medical domain, in particular to the contactless sleep evaluation method and device based on CPC.
Background technology
Sleep occupies an important role in life in people.The quality of sleep can directly affect people’s lives.Together
When, increasingly clear with the harm to sleep and the relevant disease of sleep-disorder disease, people also more pay close attention to sleeping for itself
Apnea situation in dormancy quality and sleep procedure.
And present analysis, the clinic " goldstandard " of diagnosis are Polysomnography system (Polysomnography, PSG).
It is monitored using PSG and usually requires to obtain multiclass physical sign parameters, for example, electroencephalogram, electroculogram, electromyogram, nasal airflow information, chest
And abdominal exercise, blood oxygen saturation SpO2 information, electrocardiogram, blood pressure information, sound of snoring record etc..It need to generally be glued with subject
Up to more than ten pieces of electrodes are pasted, this can form to the ortho of subject and interfere, and influence the physiology and psychological condition of subject, together
When be easily formed " first night effect " so that testing result deviates.Meanwhile PSG prices are relatively expensive, signal acquisition
Complexity need to have professional training personnel operation.It is unfavorable in common middle and small hospital and universal at home.
Invention content
The embodiment of the present invention provides a kind of contactless sleep evaluation method and device based on CPC, to improve above-mentioned ask
Topic.
To achieve these goals, technical solution used in the embodiment of the present invention is as follows：
In a first aspect, an embodiment of the present invention provides a kind of contactless sleep evaluation method based on CPC, applied to electricity
Sub- equipment, the electronic equipment are electrically connected with fine motion sensing device, the method includes：The fine motion sensing device is received to adopt
The fine motion data collected, wherein, the fine motion data are given birth to by the fine motion sensing device according to human organ microvibration signal
Into；Multiresolution wavelet conversion process is carried out to the fine motion data, to obtain heart rate monitor reference number and respiratory rate characterization signal；
Respectively corresponding heart rate sequence and respiratory rate sequence are extracted from the heart rate monitor reference number and respiratory rate characterization signal；According to institute
State heart rate sequence and respiratory rate sequence and generate corresponding coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure, be based on coherence spectrum,
Crosspower spectrum and cardiopulmonary coupling spectral figure carry out sleep evaluation.
Second aspect, an embodiment of the present invention provides a kind of contactless sleep evaluation device based on CPC, applied to electricity
Sub- equipment, the electronic equipment are electrically connected with fine motion sensing device, and described device includes：Receiving module, it is described for receiving
The collected fine motion data of fine motion sensing device, wherein, the fine motion data are by the fine motion sensing device according to human organ
Microvibration signal generates；Processing module, for carrying out multiresolution wavelet conversion process to the fine motion data, to obtain the heart
Rate characterizes signal and respiratory rate characterization signal；Extraction module, for respectively from the heart rate monitor reference number and respiratory rate characterization letter
Corresponding heart rate sequence and respiratory rate sequence are extracted in number；Generation module, for according to the heart rate sequence and respiratory rate sequence
Corresponding coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure are generated, to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral
Figure carries out sleep evaluation.
Compared with prior art, a kind of contactless sleep evaluation method based on CPC provided in an embodiment of the present invention is led to
Cross the fine motion data generated according to human organ microvibration signal for receiving the fine motion sensing device feedback.Again to described micro-
Dynamic data carry out multiresolution wavelet conversion process, to isolate heart rate monitor reference number and respiratory rate characterization signal.And according to from
In the heart rate monitor reference number and respiratory rate characterization signal the heart rate sequence that extracts and respiratory rate sequence generate corresponding coherence spectrum,
Crosspower spectrum and cardiopulmonary coupling spectral figure carry out sleep evaluation to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.Nothing
The physical sign parameters of multiple types need to be acquired, reduce the dimension and difficulty of data acquisition, the cost of equipment are also reduced, convenient for pushing away
Extensively.Simultaneously as using to the fine motion data carry out multiresolution wavelet conversion process, with isolate heart rate monitor reference number and
Respiratory rate characterizes signal, it is therefore not necessary to which fine motion sensing device is set to body surface, avoids influencing subject.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that being understood by implementing the present invention.The purpose of the present invention and other advantages are in specification, claims
And specifically noted structure is realized and is obtained in attached drawing.
For the above objects, features and advantages of the present invention is enable to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate
Appended attached drawing, is described in detail below.
Description of the drawings
It in order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range, for those of ordinary skill in the art, without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 shows the schematic diagram for the application environment that present pre-ferred embodiments provide.
Fig. 2 is the schematic diagram of electronic equipment that present pre-ferred embodiments provide.
Fig. 3 is the flow chart of a kind of contactless sleep evaluation method based on CPC that present pre-ferred embodiments provide.
Fig. 4 is the sub-step flow chart of the step S102 in Fig. 3.
Fig. 5 is the schematic diagram of a kind of contactless sleep evaluation device based on CPC that present pre-ferred embodiments provide.
Fig. 6 is the function sub-modules schematic diagram of processing module in Fig. 5.
Icon：100- electronic equipments；Contactless sleep evaluation devices of the 200- based on CPC；300- fine motion sensing devices；
111- memories；112- storage controls；113- processors；114- Peripheral Interfaces；115- input-output units；116- displays are single
Member；201- receiving modules；202- processing modules；2021- first handles submodule；2022- second processing submodules；2023-
Three processing submodules；203- extraction modules；204- generation modules.
Specific embodiment
Below in conjunction with attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.Usually exist
The component of the embodiment of the present invention described and illustrated in attached drawing can be configured to arrange and design with a variety of different herein.Cause
This, the detailed description of the embodiment of the present invention to providing in the accompanying drawings is not intended to limit claimed invention below
Range, but it is merely representative of the selected embodiment of the present invention.Based on the embodiment of the present invention, those skilled in the art are not doing
Go out all other embodiments obtained under the premise of creative work, shall fall within the protection scope of the present invention.
It should be noted that：Similar label and letter represents similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need to that it is further defined and explained in subsequent attached drawing.Meanwhile the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that instruction or hint relative importance.
Sleep occupies an important role in life in people.The quality of sleep can directly affect people’s lives.Together
When, increasingly clear with the harm to sleep and the relevant disease of sleep-disorder disease, people also more pay close attention to sleeping for itself
Dormancy quality and apnea situation.
In order to which preferably to sleep study and monitoring, the R.J.Thomas of the Sleeping Center of harvard medical school is with intersecting medicine
The scholars of team propose a kind of utilization electrocardio ECG signal and export breath signal from electrocardio QRS complex amplitude sequence
The algorithm of (ECG-Derived Respiration, EDR) is slept to assess, i.e. cardiopulmonary coupling analytical method
(Cardiopulmonary Coupling, CPC).CPC crosspower spectrums point out the energy ratio of its high frequency, low frequency and very low frequencies part
Example is different, structure (deep sleep) and sleep event (disordered breathing and sleep-respiratory low pass during sleeping available for reflection
Gas).But main not foot point is derived from the cardiac electrical QRS groups of waves of ECG existing for the CPC cardiopulmonary coupling techniques based on EDR principles
The quality of EDR breath signals is not often high, while breath signal derived from EDR and the individual difference height phase of measurement object
It closes, there may be easily asked by what the various factors such as environment, individual subject's psychology, physiology were influenced for derived breathing time sequence
Topic, this can directly influence the measurement effect of the cardiopulmonary coupling technique based on electrocardio ECG and the accuracy of analysis.
In order to reduce the dimension and difficulty of data acquisition, the cost of equipment is also reduced, convenient for promoting.Also for avoiding
Sleep evaluation result is influenced by individual difference.A kind of contactless sleep based on CPC provided in an embodiment of the present invention
Appraisal procedure and device.
The following each embodiments of the present invention can be applied in environment as shown in Figure 1 unless otherwise instructed, as shown in Figure 1,
The electronic equipment 100 is electrically connected with fine motion sensing device 300.
Above-mentioned fine motion sensing device 300 can be highly sensitive passive sensor.Above-mentioned fine motion sensing device 300 can be with
It is installed under the medium " articles for use " for the subject's trunk for being used to support the state of being lying when sleeping or comprising wherein.Above-mentioned medium " articles for use " can
With, but be not limited to include at least one of sheet, pillow, mattress, cabinet base and bedding.It can be according to the specific of medium " articles for use "
Situation selects 300 installation site of fine motion sensing device, for example, sheet and the subject's body phase for the state of being lying when sleeping can be installed on
To side, the pillow side opposite with the subject's head for the state of being lying when sleeping can be installed on, can also be embedded in pillow (or
Under) etc..Above-mentioned fine motion sensing device 300 can be used for receiving to be produced through what medium " articles for use " conducted by organs such as the cardiopulmonary of subject
Raw human organ microvibration signal.Above-mentioned fine motion sensing device 300 is according to the human organ microvibration signal received
Fine motion data are generated, so as to the sleep according to fine motion data assessment subject.Specifically, fine motion sensing device 300 is by human body device
Official's microvibration signal is converted to digitized fine motion data from physical analogy signal through " modulus " switching device.
As shown in Fig. 2, it is the block diagram of above-mentioned electronic equipment 100.Above-mentioned electronic equipment 100 can be, but not limited to
It is：PC (personal computer, PC), tablet computer, intelligent terminal, notebook tablet computer, car-mounted terminal etc.
Terminal device.Electronic equipment 100 includes contactless sleep evaluation device 200, memory 111, storage control based on CPC
112nd, processor 113, Peripheral Interface 114, input-output unit 115 and display unit 116.
The memory 111, storage control 112, processor 113, Peripheral Interface 114, input-output unit 115 and aobvious
Show that 116 each element of unit is directly or indirectly electrically connected between each other, to realize the transmission of data or interaction.For example, these
Element can be realized by one or more communication bus or signal wire be electrically connected between each other.It is described based on the non-contact of CPC
Formula sleep evaluation device 200 can be stored in the memory including at least one in the form of software or firmware (firmware)
In 111 or the software function module that is solidificated in the operating system (operating system, OS) of the electronic equipment 100.
The processor 113 is used to perform the executable module stored in the memory 111, such as described based on the non-contact of CPC
Software function module and computer program included by formula sleep evaluation device 200 etc..
Wherein, the memory 111 may be, but not limited to, random access memory (Random Access
Memory, RAM), read-only memory (Read Only Memory, ROM), programmable read only memory (Programmable
Read-Only Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only
Memory, EPROM), electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only
Memory, EEPROM) etc..Wherein, for storing program, processor 113 performs memory 111 after execute instruction is received
Described program.The processor 113 and other possible components can be in the storage controls to the access of memory 111
It is carried out under 112 control.
The processor 113 may be a kind of IC chip, have the processing capacity of signal.Above-mentioned processor can
To be general processor, including central processing unit (Central Processing Unit, CPU), network processing unit (Network
Processor, NP) etc.；It can also be digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array
Arrange (FPGA) either other programmable logic device, discrete gate or transistor logic, discrete hardware components.It can realize
Or disclosed each method, step and logic diagram in the execution embodiment of the present invention.General processor can be microprocessor
Or the processor can also be any conventional processor etc..
The Peripheral Interface 114 is by various input/output devices (such as input-output unit 115 and display unit 116)
Coupled to the processor 113 and the memory 111.In some embodiments, Peripheral Interface 114, processor 113 and
Storage control 112 can be realized in one single chip.In some other example, they can be real by independent chip respectively
It is existing.
The input-output unit 115 is used to that user input data to be supplied to realize user and the electronic equipment 100
Interaction.The input-output unit 115 may be, but not limited to, dummy keyboard, mouse etc..
The display unit 116 provided between the electronic equipment 100 and user an interactive interface (such as user behaviour
Make interface) or for display image data.In the present embodiment, the display unit 116 can be liquid crystal display or touch-control
Display.Can be the capacitance type touch control screen or electric resistance touch-control for supporting single-point and multi-point touch operation if touch control display
Screen etc..Single-point and multi-point touch operation is supported to refer to that touch control display can sense the one or more on the touch control display
The touch control operation generated at position, and processor is transferred to be calculated and handled the touch control operation that this is sensed.
First embodiment
Please refer to Fig. 3, be present pre-ferred embodiments provide be applied to electronic equipment 100 shown in Fig. 2 based on CPC
Contactless sleep evaluation method flow chart.The contactless sleep evaluation method based on CPC includes the following steps：
Step S101 receives the 300 collected fine motion data of fine motion sensing device.
Above-mentioned fine motion data are generated by the fine motion sensing device 300 according to human organ microvibration signal.
In embodiments of the present invention, it is passed from the fine motion on the medium of subject's trunk for being used to support the state of being lying when sleeping
Induction device 300 obtains fine motion data.The fine motion data mainly microvibration of subject's cardiopulmonary organ by being transmitted by medium
Signal generates.Certainly, fine motion data be also likely to be present grind turning in subject's sleep procedure toss about generation vibration cause it is certain
Error.But since grind turning tosses about and can also characterize sleep quality in sleep procedure, accordingly, there exist such error to feelings of entirely sleeping
The analysis of condition has the function of forward direction.
In other embodiments, the fine motion data of reception can also be formed on the fine motion sensing device of subject's body surface from patch
300 obtain.Here, although there is also subject's body surfaces to paste collecting device processed, the required electrode for being affixed on body surface is few, to subject
Caused by influence it is small.
Step S102, to the fine motion data carry out multiresolution wavelet conversion process, with obtain heart rate monitor reference number and
Respiratory rate characterizes signal.
Can be successively using continuous wavelet transform and discrete binary wavelet transformation to fine motion number in the embodiment of the present invention
According to being handled, heart rate monitor reference number and respiratory rate characterization signal are isolated from fine motion data.Optionally, as shown in figure 4, step
Rapid S102 may comprise steps of：
Sub-step S1021 decomposites the first heartbeat signal and first using continuous wavelet transform from the fine motion data
Breath signal.
In the present embodiment, before step S102, the method can also include determining to divide from fine motion data
Solve the continuous wavelet transform for heartbeat signal of the first heartbeat signal.Optionally it is determined that for the continuous small of heartbeat signal
The mode of wave conversion can be according to choose in advance wavelet basis function, the fine motion sensing device 300 sample frequency and the heart
It jumps energy frequency section and obtains corresponding first scale factor.According to first scale factor and the wavelet basis function, really
The fixed continuous wavelet transform for being directed to heartbeat signal.The corresponding centre frequency of wavelet basis function chosen in advance is to determine
The corresponding frequency of the peak value of its power spectral density function under scale factor.And the corresponding centre frequency of wavelet basis function chosen with
The inversely proportional relationship of scale factor, can be expressed as follows：
Wherein, FsFor 300 sample frequency of fine motion sensing device；fcThe corresponding centre frequency of wavelet basis function to choose, and
For constant.In frequency space, the main energetic (peak value) of heartbeat signal can lead to usually between 7~9Hz
It crosses above formula, sample frequency, corresponding centre frequency and is attained at best the first scale factor for heartbeat signal.Preferably, it is right
In the heartbeat signal to be obtained in sample frequency FsUnder, the centre frequency for selecting to determine wavelet basis function is 8Hz, and-three dB bandwidth is
3Hz determines the first optimal scale factor.
Further, the method can also include determining the needle for decompositing the first breath signal from fine motion data
To the continuous wavelet transform of breathing.Optionally it is determined that the mode for the continuous wavelet transform of breath signal can be according to pre-
Wavelet basis function, the sample frequency of the fine motion sensing device 300 and the breathing energy frequency section first chosen obtain corresponding
Second scale factor.According to second scale factor and the wavelet basis function, determine described for the continuous of breath signal
Wavelet transformation.Determine that the mode of the second scale factor is identical with obtaining the first scale factor principle, details are not described herein.The two area
It is not, the main energetic of breath signal is less than 1Hz.Preferably, the breath signal of acquisition is in sample frequency FsUnder, selection determines
The centre frequency of wavelet basis function is 0.6Hz, and -3dB determines optimal second scale factor for 0.4Hz.
In the present embodiment, according to fine motion data, formula is utilized：
Isolate the first heartbeat signal and the first breath signal.Wherein, a is the scale factor of continuous wavelet transform.WTf
(a, b) be wavelet conversion coefficient, characterize input signal x (t) (the fine motion data i.e. in the present embodiment), corresponding scale because
Module maximum and zero crossing under son are actually also to characterize main feature information of the input signal on scale a.When a is the
During one scale factor, WTf(a, b) represents the first heartbeat signal, when a is the second scale factor, WTf(a, b) represents the first breathing
Signal.B is preset space displacement information.ψ (t) is previously selected wavelet basis function.
Sub-step S1022, using discrete binary wavelet transformation to first heartbeat signal and the first breath signal into
Row processing, to obtain the second heartbeat signal and the second breath signal.
In embodiments of the present invention, sub-step S1021 is substantially to be changed using continuous wavelet to digital signal in difference
Signal in frequency band optimizes separation.From the perspective of Digital Signal Processing, wavelet basis function can be understood as digital sky
Interior wave filter.But physically and there is no ideal digital filter for the original signal information in different frequency bands point
From.Therefore, it is necessary to the first heartbeat signal and the first breath signal are advanced optimized using discrete binary wavelet transformation
Separation.Optionally, can be using the mode of discrete binary wavelet transformation：According to the first heartbeat signal and the first breathing letter
Number, utilize formula：
The second heartbeat signal and the second breath signal are obtained respectively.When obtaining the second heartbeat signal using above formula, x [n]
Represent the corresponding discrete signal of the first heartbeat signal.When obtaining the second breath signal using above formula, x [n] represents the first breathing
The corresponding discrete signal of signal.G [k] expression be pre-selected discrete wavelet variation the corresponding parameter of low-pass filter group to
Amount can filter the high frequency part of input signal and output low frequency part.The discrete wavelet transformer that h [k] expressions are pre-selected
The corresponding parameter vector of high-pass filter group of change can filter frequency component and export high frequency part.Therefore, xj,L[n] table
Show approximation component of the j-th stage wavelet transform to x [n], xj,H[n] represents the details to x [n] point of j-th stage wavelet transformation
Amount.From frequency domain, the discrete binary wavelet transformation of multilayer is that x [n] exists repeatedlyInterior ingredient is approximate
Half-and-half be decomposed into approximation component (low frequency part) and details coefficients (high frequency section).As can be seen that by believing the first heartbeat
Number and the first breath signal multilayer discrete binary wavelet transformation, only retain comprising two kinds of signals in the range of allocated frequency band
Other ingredients (setting to 0 processing) are abandoned in main component part.In this way, it can realize elimination or reduce doing because of " frequency overlapping "
It disturbs.Before using above formula, it is also necessary to determine that breath signal and heartbeat message are corresponding in discrete binary wavelet transformation respectively
The total number of levels of separation, K represents the total hierarchical data of corresponding separation in above formula.Preferentially, it may be predetermined that heartbeat signal
The corresponding ranging from 6~10Hz of frequency, and according to the range determine the total number of levels of the corresponding separation of heartbeat signal, retain series
And abandon number of levels (setting to 0 processing).Similarly preferably, the frequency that predefines breath signal is corresponding ranging from 0.4~
0.8Hz, and according to the range determine the total number of levels of the corresponding separation of breath signal, retain number of levels and abandon number of levels and (set to 0 place
Reason).In embodiments of the present invention, according to the total number of levels of the corresponding separation of the first heartbeat signal, heartbeat signal, retain number of levels and
Number of levels is abandoned, using above formula, obtains the second heartbeat signal.According to the first breath signal, the corresponding total layer of separation of breath signal
Series retains number of levels and abandons number of levels, using above formula, obtains the second breath signal.
Sub-step S1023 is small using corresponding binary system respectively according to second heartbeat signal and the second breath signal
Wave inverse transformation obtains the corresponding heart rate monitor reference number and respiratory rate characterization signal.
In the embodiment of the present invention, binary wavelet inversion corresponding with the discrete binary wavelet transformation of heartbeat signal is utilized
It changes and the second heartbeat signal is handled, to obtain the heart rate monitor reference number.Using small with the discrete binary of breath signal
The corresponding binary wavelet inverse transformation of wave conversion handles the second breath signal, to obtain respiratory rate characterization signal.
Step S103, respectively from the heart rate monitor reference number and respiratory rate characterization signal in extract corresponding heart rate sequence and
Respiratory rate sequence.
In embodiments of the present invention, since " causal transform " of wavelet transform process can cause heart rate monitor reference number and breathing
Rate characterizes signal has certain stationary phase to postpone relative to fine motion data.It therefore, can be according to predetermined heartbeat phase
Delay is adjusted second heartbeat signal.According to predetermined breathing phases delay to second breath signal into
Row adjustment.As a kind of embodiment, computer mathematics may be used in above-mentioned heartbeat phase delay and breathing phases delay
Know that signal carries out multiresolution wavelet conversion process, caused by being corresponded to according to the signal acquisition wavelet transformation after conversion process
Stationary phase postpones.It is obtained respectively according to second heartbeat signal after adjustment and the second breath signal again synchronous in phase
The heart rate sequence and the respiratory rate sequence.
Further, obtaining the mode of the heart rate sequence can be：Using preset newton-Ke Tesi difference filters
Second heartbeat signal after adjustment is handled, to obtain third heartbeat signal, wherein the preset newton-Ke Te
This difference filter is determined according to the sample frequency of the fine motion sensing device 300.Specifically, through following " newton-Ke Tesi "
Difference filter filters：
Y [n]=(45 2 δ of Δ δ -9 Δs+3 δ of Δ)/60
It is handled, wherein, Δ δ=x [n+ δ]-x [n- δ].δ is positive integer, it is preferable that δ access values are(whenLess than 1, then take 1).The differential amplification signal obtained by difference engine filtering described in above formula.
The third heartbeat signal is subjected to quadratic nonlinearity processing successively and 2 pre-selection power point rolling average is handled,
Wherein, the pre-selection power is determined according to the sample frequency of the fine motion sensing device 300.Specifically, by " newton-Ke Tesi "
At signal warp " square ", the non-linear of " 2 γ powers point rolling averages ", linear operation after difference filter filter and amplification
Reason.Preferably, positive integer γ access value is(whenLess than 1, take 1).Using threshold method described from treated
The heart rate monitor reference number is obtained in three heartbeat signals.
Further, obtaining the mode of the respiratory rate sequence can be：Using zero-crossing method from described after adjustment
The respiratory rate sequence is extracted in two breath signals.Specifically, rising was found out from second breath signal after adjustment
Along the zero crossing of (or failing edge), the time interval per the respiratory cycle twice in succession is obtained, and then calculate respiratory rate sequence.
Step S104 generates corresponding coherence spectrum, crosspower spectrum and cardiopulmonary according to the heart rate sequence and respiratory rate sequence
Coupling spectral figure carries out sleep evaluation to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.
When in embodiments of the present invention, due to practical application, the reason of some are complicated, is likely to result in using heart rate and exhales
Coupling principle is come when quantifying sleep state between suction rate, it may appear that certain measurement deviates.Such as heart rate and respiratory rate are accidentally surveyed, the heart
Restrain not normal, signal period internal respiration it is incomplete caused by the reasons such as secondary small breathing may all introduce error or mistake.In order to disappear
Error and mistake are removed or reduce, step S104 can be by eliminating the exception in the heart rate sequence and respiratory rate sequence respectively
Value.The mode of the above-mentioned elimination heart rate sequence and the exceptional value in respiratory rate sequence can be：It is calculated using sliding window intermediate value
Method is respectively handled the heart rate sequence and respiratory rate sequence, different in the heart rate sequence and respiratory rate sequence to eliminate
Constant value.As a kind of embodiment, on a timeline, " sliding window intermediate value " method is used respectively to heart rate sequence and respiratory rate sequence
Row are handled, the heart rate sequence and respiratory rate sequence newly obtained.Preferably, the width of window is set as 10 seconds, movement pace 1
Second, take the typical value (true value) that the intermediate value in window is current time.Further according to the heart rate sequence for eliminating exceptional value and exhale
Suction rate sequence generates normalized coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.Optionally, its normalization is calculated respectively
Coherence spectrum, crosspower spectrum and " cardiopulmonary coupling " spectrogram.On normalization " cardiopulmonary coupling " spectrogram, specific frequency model is selected
Enclose the parameter as sleep evaluation.Preferably, it is respectively very low frequencies coupling (VLFC) in three different coupling frequency bands：0.01~
0.05Hz ranges；Low frequency couples (LFC)：0.05~0.15Hz ranges and high-frequency coupling (HFC)：In the range of 0.15~0.40Hz its
The characteristic index (for example, peak value, mean value, percentage etc.) of " cardiopulmonary coupling " spectrogram is normalized as sleep state and is slept low
The assessment parameter of ventilation event.To carry out sleep apnea and sleep quality assessment.
It is commented as shown in figure 5, the embodiment of the present invention provides a kind of contactless sleep based on CPC corresponding with the above method
Estimate device 200.The above-mentioned contactless sleep evaluation device 200 based on CPC is applied to electronic equipment 100.The electronic equipment
100 are electrically connected with fine motion sensing device 300, and described device includes：
Receiving module 201, for receiving the 300 collected fine motion data of fine motion sensing device, wherein, the fine motion
Data are generated by the fine motion sensing device 300 according to human organ microvibration signal.
Processing module 202, for carrying out multiresolution wavelet conversion process to the fine motion data, to obtain heart rate characterization
Signal and respiratory rate characterization signal.
Preferably, as shown in fig. 6, processing module 202 can include：First processing submodule 2021, for using continuously
Wavelet transformation decomposites the first heartbeat signal and the first breath signal from the fine motion data.Second processing submodule 2022,
First heartbeat signal and the first breath signal are handled for being utilized respectively discrete binary wavelet transformation, to obtain
Second heartbeat signal and the second breath signal.Third handles submodule 2023, for respectively according to second heartbeat signal and
Second breath signal using corresponding binary wavelet inverse transformation, obtains the corresponding heart rate monitor reference number and respiratory rate table
Reference number.
Extraction module 203, for extracting the corresponding heart from the heart rate monitor reference number and respiratory rate characterization signal respectively
Rate sequence and respiratory rate sequence.
Generation module 204, for generating corresponding coherence spectrum, crosspower spectrum according to the heart rate sequence and respiratory rate sequence
And cardiopulmonary coupling spectral figure, carry out sleep evaluation to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device can refer to the corresponding process in preceding method embodiment, and details are not described herein.
In conclusion a kind of contactless sleep evaluation method and device based on CPC provided in an embodiment of the present invention.Its
In, the method includes receiving the collected fine motion data of fine motion sensing device, wherein, the fine motion data are by described micro-
Dynamic sensing device is generated according to human organ microvibration signal；The fine motion data are carried out at multiresolution wavelet transformation
Reason, to obtain heart rate monitor reference number and respiratory rate characterization signal；Respectively from the heart rate monitor reference number and respiratory rate characterization signal
It is middle to extract corresponding heart rate sequence and respiratory rate sequence；It is corresponding relevant according to the heart rate sequence and the generation of respiratory rate sequence
Spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure carry out sleep to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure and comment
Estimate.The physical sign parameters of multiple types need not be acquired, reduce the dimension and difficulty of data acquisition, also reduce the cost of equipment, just
In popularization.Simultaneously as multiresolution wavelet conversion process is carried out using to the fine motion data, to isolate heart rate monitor reference
Number and respiratory rate characterization signal, it is therefore not necessary to fine motion sensing device is set to body surface, avoid influencing subject.
In several embodiments provided herein, it should be understood that disclosed device and method can also pass through
Other modes are realized.The apparatus embodiments described above are merely exemplary, for example, flow chart and block diagram in attached drawing
Show the device of multiple embodiments according to the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.In this regard, each box in flow chart or block diagram can represent the one of a module, program segment or code
Part, a part for the module, program segment or code include one or more and are used to implement holding for defined logic function
Row instruction.It should also be noted that at some as in the realization method replaced, the function that is marked in box can also be to be different from
The sequence marked in attached drawing occurs.For example, two continuous boxes can essentially perform substantially in parallel, they are sometimes
It can perform in the opposite order, this is depended on the functions involved.It is it is also noted that every in block diagram and/or flow chart
The combination of a box and the box in block diagram and/or flow chart can use function or the dedicated base of action as defined in performing
It realizes or can be realized with the combination of specialized hardware and computer instruction in the system of hardware.
In addition, each function module in each embodiment of the present invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized in the form of software function module and is independent product sale or in use, can be with
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme of the present invention is substantially in other words
The part contribute to the prior art or the part of the technical solution can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, is used including some instructions so that a computer equipment (can be
People's computer, server or network equipment etc.) perform all or part of the steps of the method according to each embodiment of the present invention.
And aforementioned storage medium includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.
It should be noted that herein, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any this practical relationship or sequence.Moreover, term " comprising ", "comprising" or its any other variant are intended to
Non-exclusive inclusion, so that process, method, article or equipment including a series of elements not only will including those
Element, but also including other elements that are not explicitly listed or further include as this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
Also there are other identical elements in process, method, article or equipment including the element.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, that is made any repaiies
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.It should be noted that：Similar label and letter exists
Similar terms are represented in following attached drawing, therefore, once being defined in a certain Xiang Yi attached drawing, are then not required in subsequent attached drawing
It is further defined and is explained.
The above description is merely a specific embodiment, but protection scope of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in change or replacement, should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention described should be subject to the protection scope in claims.
Claims (10)
- A kind of 1. contactless sleep evaluation method based on CPC, which is characterized in that applied to electronic equipment, the electronics is set It is standby to be electrically connected with fine motion sensing device, the method includes：The collected fine motion data of the fine motion sensing device are received, wherein, the fine motion data are by the fine motion sensing device It is generated according to human organ microvibration signal；Multiresolution wavelet conversion process is carried out to the fine motion data, to obtain heart rate monitor reference number and respiratory rate characterization letter Number；Respectively corresponding heart rate sequence and respiratory rate sequence are extracted from the heart rate monitor reference number and respiratory rate characterization signal；Corresponding coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure are generated according to the heart rate sequence and respiratory rate sequence, with Sleep evaluation is carried out based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.
- 2. the contactless sleep evaluation method based on CPC as described in claim 1, which is characterized in that described to described micro- The step of dynamic data carry out multiresolution wavelet conversion process includes：The first heartbeat signal and the first breath signal are decomposited from the fine motion data using continuous wavelet transform；It is utilized respectively discrete binary wavelet transformation to handle first heartbeat signal and the first breath signal, to obtain Second heartbeat signal and the second breath signal；Respectively according to second heartbeat signal and the second breath signal, corresponding binary wavelet inverse transformation, acquisition pair are utilized The heart rate monitor reference number and respiratory rate the characterization signal answered.
- 3. the contactless sleep evaluation method based on CPC as claimed in claim 2, which is characterized in that the continuous wavelet Transformation includes also wrapping for the continuous wavelet transform and the continuous wavelet transform for breath signal, the method for heartbeat signal It includes：Wavelet basis function, the sample frequency of the fine motion sensing device and heartbeat energy frequency section according to choosing in advance obtain Corresponding first scale factor；According to first scale factor and the wavelet basis function, the continuous wavelet transform for being directed to heartbeat signal is determined, Wherein, the continuous wavelet transform for heartbeat signal is believed for decompositing first heartbeat from the fine motion data Number；Wavelet basis function, the sample frequency of the fine motion sensing device and breathing energy frequency section according to choosing in advance obtain Corresponding second scale factor；According to second scale factor and the wavelet basis function, the continuous wavelet transform for being directed to breath signal is determined, Wherein, the continuous wavelet transform for breath signal is believed for decompositing first breathing from the fine motion data Number.
- 4. the contactless sleep evaluation method based on CPC as claimed in claim 2, which is characterized in that respectively from the heart Corresponding heart rate sequence is extracted in rate characterization signal and respiratory rate characterization signal and respiratory rate sequence includes：Second heartbeat signal is adjusted according to the delay of predetermined heartbeat phase；Second breath signal is adjusted according to the delay of predetermined breathing phases；The synchronous heart rate in phase is obtained according to second heartbeat signal after adjustment and the second breath signal respectively Sequence and the respiratory rate sequence.
- 5. the contactless sleep evaluation method based on CPC as claimed in claim 4, which is characterized in that from the institute after adjustment The step of extracting the heart rate sequence in the second heartbeat signal is stated to include：Second heartbeat signal after adjustment is handled using preset newton-Ke Tesi difference filters, to obtain Third heartbeat signal, wherein sampling frequency of the preset newton-Ke Tesi difference filters according to the fine motion sensing device Rate determines；The third heartbeat signal is subjected to quadratic nonlinearity processing successively and 2 pre-selection power point rolling average is handled, wherein, The pre-selection power is determined according to the sample frequency of the fine motion sensing device；The heart rate monitor reference number is obtained from treated the third heartbeat signal using threshold method.
- 6. the contactless sleep evaluation method based on CPC as claimed in claim 4, which is characterized in that from the institute after adjustment The step of extracting the respiratory rate sequence in the second breath signal is stated to include：The respiratory rate sequence is extracted from second breath signal using zero-crossing method.
- 7. the contactless sleep evaluation method based on CPC as described in claim 1, which is characterized in that described in the basis The step of heart rate sequence and respiratory rate sequence generate corresponding coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure includes：The exceptional value in the heart rate sequence and respiratory rate sequence is eliminated respectively；According to the heart rate sequence of exceptional value and respiratory rate sequence is eliminated, normalized coherence spectrum, crosspower spectrum and the heart are generated Lung coupling spectral figure.
- 8. the contactless sleep evaluation method based on CPC as claimed in claim 7, which is characterized in that described to eliminate respectively The step of exceptional value in the heart rate sequence and respiratory rate sequence, includes：The heart rate sequence and respiratory rate sequence are handled respectively using sliding window median algorithm, to eliminate the heart rate Exceptional value in sequence and respiratory rate sequence.
- 9. a kind of contactless sleep evaluation device based on CPC, which is characterized in that applied to electronic equipment, the electronics is set Standby to be electrically connected with fine motion sensing device, described device includes：Receiving module, for receiving the collected fine motion data of the fine motion sensing device, wherein, the fine motion data are by described Fine motion sensing device is generated according to human organ microvibration signal；Processing module, for the fine motion data carry out multiresolution wavelet conversion process, with obtain heart rate monitor reference number and Respiratory rate characterizes signal；Extraction module, for respectively from the heart rate monitor reference number and respiratory rate characterization signal in extract corresponding heart rate sequence and Respiratory rate sequence；Generation module, for generating corresponding coherence spectrum, crosspower spectrum and cardiopulmonary according to the heart rate sequence and respiratory rate sequence Coupling spectral figure carries out sleep evaluation to be based on coherence spectrum, crosspower spectrum and cardiopulmonary coupling spectral figure.
- 10. the contactless sleep evaluation device based on CPC as claimed in claim 9, which is characterized in that the processing module Including：First processing submodule, for decompositing the first heartbeat signal and the from the fine motion data using continuous wavelet transform One breath signal；Second processing submodule breathes first heartbeat signal and first for being utilized respectively discrete binary wavelet transformation Signal is handled, to obtain the second heartbeat signal and the second breath signal；Third handles submodule, for respectively according to second heartbeat signal and the second breath signal, using corresponding two into Wavelet inverse transformation processed obtains the corresponding heart rate monitor reference number and respiratory rate characterization signal.
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