CN111444797B - Non-contact heart rate detection method - Google Patents
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Abstract
According to the non-contact heart rate detection method, the chrominance characteristic S is firstly calculated for the signal acquired by the camera 1 (t) and S 2 (t) by the colorimetric characteristics S 1 (t) and S 2 (t) preprocessing and extracting each path of signal to obtain pulse signals h (t) and h 1 (t) and h 2 (t), and then the extracted pulse signal h 1 (t) and h 2 (t) adopting FastICA algorithm to further separate blind sources, and utilizing pulse signals h (t) and h 1 (t) and h 2 (t) determining the kurtosis value of the power spectrum as a blind source separation result, and in addition, when the kurtosis value of the power spectrum of the signal is close, selecting the signal by using the kurtosis value easily and wrongly, and using the signal-to-noise ratio as an index can be helpful for completing the signal selection; therefore, the invention can effectively process noise interference caused by illumination change and involuntary movement of a subject, obtain a signal with lower noise and improve the anti-interference performance and the measurement precision of detection.
Description
Technical Field
The application relates to the technical field of signal processing, in particular to a non-contact heart rate detection method.
Background
The heart rate refers to the number of beats per minute of the heart, and modern medicine finds that the slower the heart rate is, the longer the life of the animal is; heart rate is an important index of health, currently, the most used clinical devices are patch type heart rate detectors, which extract heart rate from human body electrical signals, although the patch type heart rate detectors have high precision, the patch type heart rate detectors must be in contact with human body when in use, which causes great inconvenience to certain people, such as heart rate monitoring of newborn babies; therefore, the video-based non-contact heart rate detection has a wide application prospect in the field of medical health, however, the video-based non-contact heart rate detection is easily interfered by noise, such as illumination change, involuntary movement of a subject, and the like, which makes it difficult to effectively extract signals, and may cause the accuracy and stability of heart rate measurement to be reduced, and therefore, a heart rate detection method capable of resisting interference and improving the measurement accuracy is required.
Disclosure of Invention
The purpose of this application lies in solving one of the technical problem that exists among the prior art at least, for this reason, this application provides non-contact heart rate detection method, improves non-contact heart rate detection's interference immunity and measurement accuracy.
The technical scheme adopted by the invention for solving the technical problems is as follows:
according to an embodiment of the invention, there is provided a non-contact heart rate detection method, comprising the steps of:
acquiring a video signal, and selecting a skin color region ROI1 from a video frame image by adopting a skin color detection algorithm;
step two, dividing the skin color area ROI1 into at least two different skin color areas ROI2 and ROI3 to generate corresponding RGB observation signals;
thirdly, filtering and time normalization preprocessing are carried out on the RGB observation signals, and primary color separation is carried out on three color channels of the RGB observation signals to obtain three-channel data of green G (t), blue B (t) and red R (t);
step four, calculating the chromaticity characteristics S of the skin color area ROI1, the skin color area ROI2 and the skin color area ROI3 1 (t) and S 2 (t)，S 1 (t)＝G(t)-B(t)，S 2 (t)＝G(t)+B(t)-2R(t)；
Step five, calculating the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 to be respectively alignedCorresponding pulse signals h (t), h 1 (t) and h 2 (t)，h(t)＝S 1 (t)+α·S 2 (t)；
Step six, pulse signals h are corrected 1 (t) and pulse signal h 2 (t) further performing blind source separation to obtain pulse signal Y 1 (t) and Y 2 (t)；
Step seven, calculating pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis and signal-to-noise ratio of the power spectrum;
step eight, comparing the pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis value and SNR of power spectrum, when pulse signals h (t) and Y 1 (t) or Y 2 (t) when the kurtosis value and the signal-to-noise ratio of a group of component signals are simultaneously maximum, the component is the acquired BVP signal; otherwise, the pulse signal h (t) is taken as the BVP signal.
The non-contact heart rate detection method provided by the embodiment of the invention at least has the following beneficial effects: in the invention, the signal collected by the camera is firstly calculated to obtain the chrominance characteristic S 1 (t) and S 2 (t) by the colorimetric characteristics S 1 (t) and S 2 (t) preprocessing and extracting each path of signal to obtain pulse signals h (t) and h 1 (t) and h 2 (t), and then the extracted pulse signal h 1 (t) and h 2 (t) adopting a FastICA algorithm to further carry out blind source separation, meanwhile, because the pulse signals have obvious quasi-periodicity, the power spectrum of the pulse signals can have very obvious spectral peaks in the heart rate frequency range, the corresponding kurtosis value is usually larger, the other signal component does not have obvious spectral peaks in the heart rate frequency range, and the corresponding kurtosis value of the power spectrum is relatively lower, so the pulse signals h (t) and h are utilized 1 (t) and h 2 (t) the kurtosis value of the power spectrum is used for judging the blind source separation result, in addition, when the kurtosis of the power spectrum of the signal is close, the signal is selected by mistake easily only by using the kurtosis value, so that the signal-to-noise ratio is also used as an index to be helpful for completing the signal selection; therefore, the invention can effectively process noise interference caused by illumination change and involuntary movement of a subject, and obtain a signal with lower noiseHigh anti-interference performance and high measurement precision.
According to some embodiments of the invention, the skin color region is segmented using approximately halving.
According to some embodiments of the invention, the kurtosis value is calculated by:
wherein,
x (n) is an input signal; and N is the number of sampling points.
According to some embodiments of the invention, the snr is calculated by:
wherein S (f) is the frequency spectrum of the extracted pulse signal, (U) t (f) The passband of the spectral peak.
According to some embodiments of the invention, the passband bandwidth of the spectral peak is 0.4Hz.
According to some embodiments of the invention, wherein
According to some embodiments of the invention, when the color type of the video frame collected by the camera is an RGB type, the three color channels are directly subjected to primary color separation; when the color type of the video frame collected by the camera is not the RGB type, the video frame is converted into the RGB color type, and then the primary colors are separated.
According to some embodiments of the invention, the sampling frequency of the camera is 30Hz/s.
According to some embodiments of the invention, the camera is located no more than 1 meter away from the subject.
According to some embodiments of the present invention, the photographing region of the camera is skin at any region of the subject.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a spectrum diagram of a pulse signal h (t) according to an embodiment of the present invention;
FIG. 3 shows a pulse signal h according to an embodiment of the present invention 1 (t) and h 2 (t) mixed spectrogram;
FIG. 4 shows a pulse signal Y according to an embodiment of the present invention 1 (t) a spectrogram;
FIG. 5 shows a pulse signal Y according to an embodiment of the present invention 2 (t) spectrogram.
Detailed Description
Reference will now be made in detail to the present preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout.
In the description of the present invention, unless explicitly defined otherwise, terms such as calculating, obtaining, sampling, corresponding and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the terms in the present invention by combining the specific contents of the technical solutions.
As shown in fig. 1, a non-contact heart rate detection method provided in an embodiment of the present application includes the following steps:
a method of non-contact heart rate detection is provided, comprising the steps of:
acquiring a video signal, and selecting a skin color region ROI1 from a video frame image by adopting a skin color detection algorithm;
dividing a skin color region ROI1 into at least two different skin color regions ROI2 and ROI3 to generate corresponding RGB observation signals;
thirdly, filtering and time normalization preprocessing are carried out on the RGB observation signals, and primary color separation is carried out on three color channels of the RGB observation signals to obtain three-channel data of green G (t), blue B (t) and red R (t);
step four, calculating the chromaticity characteristics S of the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 1 (t) and S 2 (t)，S 1 (t)＝G(t)-B(t)，S 2 (t)＝G(t)+B(t)-2R(t)；
Step five, calculating pulse signals h (t), h corresponding to the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 respectively 1 (t) and h 2 (t)，h(t)＝S 1 (t)+α·S 2 (t) in which
Step six, pulse signals h are corrected 1 (t) and pulse signal h 2 (t) further performing blind source separation to obtain pulse signal Y 1 (t) and Y 2 (t)；
Step seven, calculating pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis value and signal-to-noise ratio of the power spectrum, wherein the kurtosis value is calculated by the formula:
wherein,
x (n) is an input signal; n is the number of sampling points; the calculation formula of the signal-to-noise ratio is as follows:
wherein S (f) is the frequency spectrum of the extracted pulse signal, (U) t (f) A passband at the peak of the spectrum; the kurtosis factor is used for representing the smoothness degree of a waveform and describing the distribution of variables, the kurtosis of normal distribution is equal to 3, the distribution curve is relatively flat when the kurtosis is less than 3, and the distribution curve is relatively steep when the kurtosis is more than 3;
step eight, comparing the pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis value and signal-to-noise ratio of power spectrum, when pulse signals h (t) and Y 1 (t) or Y 2 (t) one group ofWhen the kurtosis value and the signal-to-noise ratio of the component signal are simultaneously maximum, the component is the acquired BVP signal; otherwise, the pulse signal h (t) is taken as the BVP signal. In the invention, the signal collected by the camera is firstly calculated to obtain the chrominance characteristic S 1 (t) and S 2 (t) by the colorimetric characteristics S 1 (t) and S 2 (t) preprocessing and extracting each path of signal to obtain pulse signals h (t) and h 1 (t) and h 2 (t), and then the extracted pulse signal h 1 (t) and h 2 (t) adopting a FastICA algorithm to further carry out blind source separation, meanwhile, because the pulse signals have obvious quasi-periodicity, the power spectrum of the pulse signals can have very obvious spectral peaks in the heart rate frequency range, the corresponding kurtosis value is usually larger, the other signal component does not have obvious spectral peaks in the heart rate frequency range, and the corresponding kurtosis value of the power spectrum is relatively lower, so the pulse signals h (t) and h are utilized 1 (t) and h 2 (t) the kurtosis value of the power spectrum is used for judging the blind source separation result, in addition, when the kurtosis of the power spectrum of the signal is close, the signal is selected by mistake easily only by using the kurtosis value, so that the signal-to-noise ratio is also used as an index to be helpful for completing the signal selection; therefore, compared with the traditional bar code correction mode, the method firstly extracts the pulse signals and then carries out blind source separation; and the kurtosis value and the signal-to-noise ratio are used as indexes to select signals, so that noise interference caused by illumination change and involuntary movement of a subject can be effectively processed, signals with lower noise are obtained, and the anti-interference performance and the measurement accuracy of detection are improved.
In another embodiment of the present invention, the skin color area is divided into two regions by approximately bisecting the skin color area, and if the skin color area is divided into three regions, the skin color area is approximately halved.
As shown in fig. 2-5, in one embodiment of the present invention, the sampling frequency of the camera is set to 30Hz/s, and the distance from the camera to the tested object is 1 meter, but of course, other distances are also possible; shooting the skin of the tested object by a camera to obtain a video signal, and collecting the video signal from a video frame image by adopting a skin color detection algorithmAn interested skin color region ROI1, equally dividing the skin color region ROI1 into two different skin color regions ROI2 and ROI3 to generate corresponding RGB observation signals, carrying out filtering and time normalization pretreatment on the RGB observation signals, and carrying out primary color separation on three color channels of the RGB observation signals to obtain three-channel data of green G (t), blue B (t) and red R (t); calculating pulse signals h (t), h corresponding to the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 respectively 1 (t) and h 2 (t)，h(t)＝S 1 (t)+α·S 2 (t) in which
As shown in fig. 2, it is a spectrogram of a pulse signal h (t), and it can be seen from the spectrogram that the extracted pulse signal h (t) is severely interfered by noise, and a frequency value corresponding to a main peak of a frequency spectrum is not a pulse frequency measured this time; further, the pulse signals h are respectively corrected 1 (t) and h 2 (t) adopting a FastICA algorithm to further carry out blind source separation, and respectively obtaining independent component pulse signals Y of the two regions which are more accurate 1 (t) and Y 2 (t), as shown in FIG. 3, FIG. 3 shows the pulse signal h 1 (t) and h 2 (t) mixed spectrum, as shown in FIGS. 4-5, FIG. 4 is the independent component pulse signal Y 1 (t), FIG. 5 shows the pulse signal Y of the independent component 2 (t), the corresponding pulse wave signal Y can be seen from FIG. 4 1 (t) has a more pronounced pulse signal than the pulse wave signal h (t) of fig. 2. H (t) of FIG. 2 and Y of FIG. 4 1 (t) and Y of FIG. 5 2 The kurtosis of the power spectrum of (t) is 10.23,22.98 and 10.29, respectively, and the corresponding signal-to-noise ratios are 0.19,0.45 and 0.21, respectively. Thus, the independent component pulse signal Y 1 (t) has the highest kurtosis and signal-to-noise ratio, so that the pulse signal Y is an independent component 1 And (t) the corresponding time domain signal can be used as an effective pulse signal.
In another embodiment of the present invention, the video signal is captured by a camera, and specifically, a camera of a mobile phone can be used for shooting.
In another embodiment of the invention, when the color type of the video frame collected by the camera is an RGB type, the three color channels are directly subjected to primary color separation; when the color type of the video frame collected by the camera is not the RGB type, the video frame is converted into the RGB color type, and then the primary colors are separated.
In another embodiment of the present invention, the distance between the camera and the object to be photographed is not more than 1 meter, which is limited by the resolution and the lens focal length of a general camera, and the shooting distance is set to not more than 1 meter in this embodiment, however, when a camera with better resolution and lens focal length is selected, the distance between the camera and the object to be photographed can be more than 1 meter.
In another embodiment of the invention, the shooting area of the camera is the skin of any area of the object to be shot, when a skin area is selected for shooting, and when the limbs of the object to be tested do not move autonomously, the shooting area can leave the shooting visual field range, and the shooting area needs to be readjusted to recover the previous shooting area.
The above is only a preferred embodiment of the present invention, but the present invention is not limited to the above embodiments, and the technical effects of the present invention can be achieved by any means which are the same or similar, and all of which are within the scope of the present invention.
Claims (8)
1. The non-contact heart rate detection method is characterized by comprising the following steps of:
acquiring a video signal, and selecting a skin color region ROI1 from a video frame image by adopting a skin color detection algorithm;
step two, dividing the skin color area ROI1 into at least two different skin color areas ROI2 and ROI3 to generate corresponding RGB observation signals;
thirdly, filtering and time normalization preprocessing are carried out on the RGB observation signals, and primary color separation is carried out on three color channels of the RGB observation signals to obtain three-channel data of green G (t), blue B (t) and red R (t);
fourthly, calculating the chromaticity characteristics S of the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 1 (t) and S 2 (t)，S 1 (t)＝G(t)-B(t)，S 2 (t)＝G(t)+B(t)-2R(t)；
Step five, calculating pulse signals h (t), h corresponding to the skin color region ROI1, the skin color region ROI2 and the skin color region ROI3 respectively 1 (t) and h 2 (t)，h(t)＝S 1 (t)+α·S 2 (t)；
Step six, pulse signals h are corrected 1 (t) and pulse signal h 2 (t) further performing blind source separation to obtain pulse signal Y 1 (t) and Y 2 (t)；
Step seven, calculating pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis and signal-to-noise ratio of the power spectrum;
step eight, comparing the pulse signals h (t) and Y 1 (t) and Y 2 (t) kurtosis value and SNR of power spectrum, when pulse signals h (t) and Y 1 (t) or Y 2 (t) when the kurtosis value and the signal-to-noise ratio of a group of component signals are simultaneously maximum, the component is the acquired BVP signal; otherwise, taking the pulse signal h (t) as a BVP signal;
in step 7, the kurtosis value is calculated by the following formula:
wherein,
x (n) is an input signal; n is the number of sampling points;
in said step 5, wherein
2. The method for non-contact heart rate detection according to claim 1, wherein in the step 1, the skin color region is divided into regions by approximately bisection.
3. Contactless heart rate system of claim 1The detection method is characterized in that, in the step 7, the calculation formula of the signal-to-noise ratio is as follows:
wherein S (f) is the frequency spectrum of the extracted pulse signal, (U) t (f) The passband of the spectral peak.
4. The method of claim 3, wherein the passband bandwidth of the spectral peak is 0.4Hz.
5. The non-contact heart rate detection method according to claim 2, wherein when the color type of the video frame collected by the camera is an RGB type, the three color channels are directly subjected to primary color separation; when the color type of the video frame collected by the camera is not the RGB type, the video frame is converted into the RGB color type, and then the primary colors are separated.
6. The method of claim 5, wherein the sampling frequency of the camera is 30Hz/s.
7. The non-contact heart rate detection method according to claim 6, wherein the distance between the camera and the shot object is not more than 1 meter.
8. The non-contact heart rate detection method according to claim 7, wherein the photographing region of the camera is skin at any region of a subject to be photographed.
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