CN104138254A - Non-contact type automatic heart rate measurement system and measurement method - Google Patents
Non-contact type automatic heart rate measurement system and measurement method Download PDFInfo
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Abstract
The invention relates to the field of electronic health detection, and discloses a non-contact type automatic heart rate measurement system and a measurement method. The non-contact type automatic heart rate measurement system adopts a non-contact mode to remotely collect video data of a measured person and performs data conversion to realize automatic heart rate measurement, and is characterized by comprising a video collection module, a framing extraction ROI (region of interest) module, a primary color component separation module, a time-domain signal generation module, a blind source separation module, a signal screening module and a heart rate analysis module. Compared with the prior art, the non-contact type automatic heart rate measurement system and the measurement method are based on an automatic face track and blind source separation technology, adopt a noninvasive and non-contact type remote physiological signal detection method, overcome influence of motion artifact in video record, has motion tolerance, is high in measurement accuracy, and can perform heart rate measurement automatically and simultaneously.
Description
Technical field
The present invention relates to electronic health care detection field, particularly relate to a kind of contactless electronic health detecting system and measuring method.
Background technology
At present, the heartbeat measuring technique that the electrocardiogram (ECG) of take is standard need to be pasted gel bonding die or chest and back belt at patient, and these contacts may cause skin allergy or discomfort.And remote measurement can provide more comfortable electrodeless physiological evaluation.But up to the present, the An attempt of design of all long-range survey systems is Shi Fei automatization nearly all, and is in use subject to the impact of motion artifacts, causes the certainty of measurement not high.
Summary of the invention
Based on above-mentioned technical problem, the present invention proposes a kind of contactless automatic heart rate measuring system and measuring method, this system by Remote Non-touch obtain the color recording of people's face, carry out people's face and each Color Channel signal is separated into independently signal component from motion tracking is separated with blind source, after analyzing and processing, can obtain metrical information, even, in the situation that motion artifacts exists, it still has degree of precision.
A kind of contactless automatic heart rate measuring system the present invention proposes, utilize cordless remote collection measured video data, carry out data transaction, realizing automatic heart rate measures, this system comprises video acquisition module, and minute frame extracts ROI module, primary color component separation module, time-domain signal generation module, blind source separation module, signal screening module, heart rate analysis module;
Described video acquisition module, for recording one section of color video frequency image that comprises whole human face region by photographic head;
Within described minute, frame extracts ROI module, for utilizing Face tracking algorithm to extract the ROI area image of the every frame picture of video;
Described primary color component separation module, carries out the separation of RGB primary colours for all ROI area images to extracted, and every color image frame generates three width gray level images, obtains three groups of primary color component images of ROI area image;
Described time-domain signal generation module, for the RGB three primary colours component image of every frame ROI area image is got respectively to the gray average of all pixels, as the eigenvalue of this two field picture, generates three time-domain signal x that time-domain signal is red channel
1(t), the time-domain signal x of green channel
2(t), the time-domain signal x of blue channel
3(t);
Described blind source separation module, for to the original time-domain signal x obtaining
1(t), x
2(t), x
3(t) carry out noise elimination, above-mentioned three time-domain signals are carried out to the separation of blind source, obtain three independently time-domain signals
Described signal screening module, for by isolated three the independent time-domain signals in blind source
respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis, choose the signal with its dependency maximum
{ 1,2,3}, as final screening signal for i ∈;
Described heart rate analysis module, for carrying out spectrum analysis generating power spectrogram to screening signal; In power spectrum chart, find out the crest frequency in assigned frequency band, the respective frequencies using main crest value frequency as heart rate, converts to this frequency, and reduction formula is: heart rate=gained frequency * 60, finally obtain heart rate measurements.
Described primary color component separation module, separated for extracted all ROI area images being carried out to CMYK primary colours, obtain four groups of primary color component images of ROI area image, and by described time-domain signal generation module, generate four time-domain signal x that time-domain signal is C-channel
c(t), the time-domain signal x of M passage
m(t), the time-domain signal x of Y passage
yand the time-domain signal x of K passage (t)
k(t).
When described four groups of primary color component images are carried out to signal screening, will carry out correlation analysis with green channel signal and change and do to carry out correlation analysis with Y channel signal.
The color type of the video image of described color video acquisition module collection comprises that RGB type and non-RGB type all can;
If the video image color type gathering is RGB type, directly by primary color component separation module, all ROI area images are carried out to RGB separation;
If video image color type is non-RGB, after first its all ROI area images being converted into RGB color type, carry out again primary colours separation, obtain the RGB primary color component image of every frame ROI image.
The invention allows for a kind of contactless automatic heart rate measuring method, utilize cordless remote collection quilt, survey person's video data, carry out data transaction, realize automatic heart rate and measure, it is characterized in that, this system comprises the following steps:
Step 1, gathers the color video frequency image that comprises human face region;
Step 2, carries out face tracking location to the video image gathering, and finds out the ROI human face region image of the every two field picture of video and extracts;
Step 3, carries out primary colours separation by the ROI area image extracting according to tri-Color Channels of RGB;
Step 4, gets respectively the gray average of all pixels to every two field picture of obtain three groups of primary color component images, as the eigenvalue of this two field picture, generates three time-domain signal x that time-domain signal is red channel
1(t), the time-domain signal x of green channel
2(t), the time-domain signal x of blue channel
3(t);
Step 5, carries out the separation of blind source to the time-domain signal obtaining;
Step 6, three that the separation of blind source is obtained are time-domain signal independently
screen, respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis, choose the signal with its dependency maximum
{ 1,2,3}, as final screening signal for i ∈;
Step 7, carries out spectrum analysis to the signal filtering out, and mates corresponding crest frequency, as the respective frequencies of heart rate, this frequency is converted, and finally obtains heart rate measurements.
The described step that the ROI area image extracting is carried out to primary colours separation according to tri-Color Channels of RGB, by the ROI area image extracting is replaced according to the step of CMYK Color Channel primary colours separation, obtain four groups of primary color component images of ROI area image, and by described time-domain signal generation module, generate four time-domain signal x that time-domain signal is C-channel
c(t), the time-domain signal x of M passage
m(t), the time-domain signal x of Y passage
yand the time-domain signal x of K passage (t)
k(t).
When described four groups of primary color component images are carried out to signal screening, will carry out correlation analysis with green channel signal and change and do to carry out correlation analysis with Y channel signal.
The color type of described color video frequency image comprises that RGB type and non-RGB type all can;
If the video image color type gathering is RGB type, directly by primary color component separation module, all ROI area images are carried out to RGB separation;
If video image color type is non-RGB, after first its all ROI area images being converted into RGB color type, carry out again primary colours separation, obtain the RGB primary color component image of every frame ROI image.
Compared with prior art, the present invention is based on people's face from motion tracking and blind source separate technology, adopt the method for noinvasive, contactless remote detection physiological signal, overcome the impact of motion artifacts in videograph, motion is had to tolerance, certainty of measurement is high, can carry out automatically many people simultaneously and automatically carry out heart rate measurement.
Accompanying drawing explanation
Fig. 1 is contactless automatic heart rate measuring system functional block diagram of the present invention.
Fig. 2 is this contactless automatic heart rate measuring method flow chart.
The specific embodiment
Below in conjunction with accompanying drawing and preferred embodiment, to according to the specific embodiment provided by the invention, structure, feature and effect thereof, be described in detail as follows.
As shown in Figure 1, be contactless automatic heart rate measuring system functional block diagram of the present invention.
Video acquisition module 11 adopts common photographic head or takes the color video that the higher special camera collection of precision comprises human face region; Divide frame to extract ROI module 12, according to Face tracking algorithm, the video of video acquisition module collection is carried out to face tracking location, extract the ROI(human face region of the every two field picture of video); By primary color component separation module 13 by the ROI(human face region extracting) according to tri-Color Channels of RGB, carry out primary colours separation, every color image frame generates three width gray level images, obtains ROI(human face region) three groups of primary color component images; Every two field picture of three groups of primary color component images that 14 pairs of time-domain signal generation modules obtain is got respectively the gray average of all pixels, as the eigenvalue of this two field picture, generates three time-domain signals of describing human face region changing features; Blind source separation module 15 adopts ICA method to carry out the separation of blind source to the time-domain signal obtaining, and eliminates partial noise, obtains three new, separate time-domain signals; Signal screening module 16 is screened separated three signals that obtain in blind source according to the dependency with green channel primary signal, obtains maximally related signal as the signal of final heart rate analysis; Described blind source separation module 15, for to the original time-domain signal x obtaining
1(t), x
2(t), x
3(t) carry out noise elimination, above-mentioned three time-domain signals are carried out to the separation of blind source, obtain three independently time-domain signals
specific practice is: by isolated three the independent time-domain signals in blind source
respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis, choose the signal with its dependency maximum
i ∈ 1,2,3}, and because green or gold-tinted (510-590nm) are the most responsive to blood pulses, the heart rate signal comprising in green channel signal is the strongest, thus this module separation of blind source is obtained three time-domain signal independently, respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis.
After above-mentioned processing finishes, the signal that 17 pairs of signal screening modules of heart rate analysis module filter out carries out spectrum analysis, finds out the crest frequency in assigned frequency band in power spectrum and, as the respective frequencies of heart rate, this frequency is converted, and finally obtains heart rate value.Specific practice is: described heart rate analysis module, and for the signal filtering out is carried out to spectrum analysis, generating power spectrogram; In power spectrum chart, find out the crest frequency in assigned frequency band, as the respective frequencies of heart rate, this frequency is converted, finally obtain heart rate value.This assigned frequency band and conversion relation can be obtained by experiment statistics.
Above-mentioned steps also can be implemented by following manner:
1, " RGB color mode " in primary color component separation module made into other color modes (as CMYK pattern), if adopt CMYK color model, generate four original mixed signals, need to change and do to carry out correlation analysis with Y channel signal carrying out correlation analysis with green channel signal in signal screening module;
If the collection video signal receiving in 2 primary color component separation modules, its color type is RGB type, and all ROI area images that directly a upper module obtained carry out RGB separation; If video image color type is non-RGB (as YUV), carry out again primary colours separation after being translated into RGB color type, obtain the RGB primary color component image of every frame ROI image;
3, " ICA method " in the separation module of blind source made into other blind source separation methods, as nonlinear blind source separation method.Consider that each signal of human body may be nonlinear, also can adopt the blind source separation method of nonlinear properties.
Claims (8)
1. a contactless automatic heart rate measuring system, utilize cordless remote collection measured video data, carry out data transaction, realizing automatic heart rate measures, it is characterized in that, this system comprises video acquisition module, and minute frame extracts ROI module, primary color component separation module, time-domain signal generation module, blind source separation module, signal screening module, heart rate analysis module;
Described video acquisition module, for recording one section of color video frequency image that comprises whole human face region by photographic head;
Within described minute, frame extracts ROI module, for utilizing Face tracking algorithm to extract the ROI area image of the every frame picture of video;
Described primary color component separation module, carries out the separation of RGB primary colours for all ROI area images to extracted, and every color image frame generates three width gray level images, obtains three groups of primary color component images of ROI area image;
Described time-domain signal generation module, for the RGB three primary colours component image of every frame ROI area image is got respectively to the gray average of all pixels, as the eigenvalue of this two field picture, generates three time-domain signal x that time-domain signal is red channel
1(t), the time-domain signal x of green channel
2(t), the time-domain signal x of blue channel
3(t);
Described blind source separation module, for to the original time-domain signal x obtaining
1(t), x
2(t), x
3(t) carry out noise elimination, above-mentioned three time-domain signals are carried out to the separation of blind source, obtain three independent time-domain signals
Described signal screening module, for by isolated three the independent time-domain signals in blind source
respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis, choose the signal with its dependency maximum
{ 1,2,3}, as final screening signal for i ∈;
Described heart rate analysis module, for carrying out spectrum analysis generating power spectrogram to screening signal; In power spectrum chart, find out the crest frequency in assigned frequency band, the respective frequencies using the first crest frequency as heart rate, converts according to this frequency, and reduction formula is: heart rate=gained frequency * 60, finally obtain heart rate measurements.
2. contactless automatic heart rate measuring system as claimed in claim 1, it is characterized in that, described primary color component separation module, separated for extracted all ROI area images being carried out to CMYK primary colours, obtain four groups of primary color component images of ROI area image, and by described time-domain signal generation module, generate four time-domain signal x that time-domain signal is C-channel
c(t), the time-domain signal x of M passage
m(t), the time-domain signal x of Y passage
y(t) the time-domain signal x of K passage
k(t).
3. contactless automatic heart rate measuring system as claimed in claim 2, is characterized in that, when described four groups of primary color component images are carried out to signal screening, will carry out correlation analysis with green channel signal and change and do to carry out correlation analysis with Y channel signal.
4. contactless automatic heart rate measuring system as claimed in claim 1, is characterized in that, the color type of the video image of described color video acquisition module collection comprises that RGB type and non-RGB type all can;
If the video image color type gathering is RGB type, directly by primary color component separation module, all ROI area images are carried out to RGB separation;
If video image color type is non-RGB, after first its all ROI area images being converted into RGB color type, carry out again primary colours separation, obtain the RGB primary color component image of every frame ROI image.
5. a contactless automatic heart rate measuring method, utilizes cordless remote collection measured video data, carries out data transaction, realizes automatic heart rate and measures, and it is characterized in that, this system comprises the following steps:
Step 1, gathers the color video frequency image that comprises human face region;
Step 2, carries out face tracking location to the video image gathering, and finds out the ROI human face region image of the every two field picture of video and extracts;
Step 3, carries out primary colours separation by the ROI area image extracting according to tri-Color Channels of RGB;
Step 4, gets respectively the gray average of all pixels to every two field picture of obtain three groups of primary color component images, as the eigenvalue of this two field picture, generates three time-domain signal x that time-domain signal is red channel
1(t), the time-domain signal x of green channel
2(t), the time-domain signal x of blue channel
3(t);
Step 5, carries out the separation of blind source to the time-domain signal obtaining;
Step 6, three independent time-domain signals that the separation of blind source is obtained
x
screen, respectively with the time-domain signal x of green channel
2(t) carry out correlation analysis, choose the signal with its dependency maximum
{ 1,2,3}, as final screening signal for i ∈;
Step 7, carries out spectrum analysis to the signal filtering out, and mates corresponding crest frequency, as the respective frequencies of heart rate, this frequency is converted, and finally obtains heart rate measurements.
6. contactless automatic heart rate measuring method as claimed in claim 1, it is characterized in that, the described step that the ROI area image extracting is carried out to primary colours separation according to tri-Color Channels of RGB, by the ROI area image extracting is replaced according to the step of CMYK Color Channel primary colours separation, obtain four groups of primary color component images of ROI area image, and by described time-domain signal generation module, generate four time-domain signal x that time-domain signal is C-channel
c(t), the time-domain signal x of M passage
m(t), the time-domain signal x of Y passage
yand the time-domain signal x of K passage (t)
k(t).
7. contactless automatic heart rate measuring method as claimed in claim 6, is characterized in that, when described four groups of primary color component images are carried out to signal screening, will carry out correlation analysis with green channel signal and change and do to carry out correlation analysis with Y channel signal.
8. contactless automatic heart rate measuring method as claimed in claim 1, is characterized in that, the color type of described color video frequency image comprises that RGB type and non-RGB type all can;
If the video image color type gathering is RGB type, directly by primary color component separation module, all ROI area images are carried out to RGB separation;
If video image color type is non-RGB, after first its all ROI area images being converted into RGB color type, carry out again primary colours separation, obtain the RGB primary color component image of every frame ROI image.
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