Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211000182-6.doi: 10.11896/jsjkx.211000182

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Non-contact Heart Rate Detection Based on Facial Video

ZENG Zi-lin1, HU Zhi-gang1,3, SHANG Peng2, WANG Xin-zheng1, FU Dong-liao1   

  1. 1 School of Medical Technology and Engineering,Henan University of Science and Technology,Luoyang,Henan 471023,China
    2 Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,Guangdong 518055,China
    3 Henan Engineering Research Center of Intelligent Rehabilitation Robot,Luoyang,Henan 471023,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:ZENG Zi-lin,born in 1998,postgra-duate.Her main research interests include medical image processing and rehabilitation robot.
    HU Zhi-gang,born in 1972,Ph.D,professor,Ph.D supervisor.His main research interests include three-dimensional reconstruction and computational biomechanics,biomedical robots.
  • Supported by:
    Key Science and Technology Program of Hennan Province,China(182102410046) and Shenzhen Science and Technology Project(JCYJ20180507182446643).

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Abstract: Non-contact facial heart rate detection based on video is susceptible to interference from ambient light and motion artifacts,and the accuracy of heart rate detection results is low.To address the above problems,this paper proposes an adaptive thresholding denoising method which combines ensemble empirical mode decomposition(EEMD) and standardized Euclidean distance to reduce external interference and improve accuracy.Firstly,the green channel pixel mean is selected as PPG signal from RGB image model recorded by camera,and then the signal is preprocessed with a filter to eliminate the signals outside the heart rate range.Secondly,the EEMD is combined with standardized Euclidean distance to threshold and reconstruct the intrinsic modal function.Finally,power spectrum analysis with Fourier transform is performed to calculate the heart rate.Experiments show that,compared with the methods based on wavelet transform and empirical mode decomposition with adaptive,this method has better stability and accuracy in denoising of non-contact facial heart rate detection,improves the robustness of heart rate detection,which is suitable for daily non-contact real-time heart rate monitoring.

Key words: Heart rate measurement, EEMD, Euclidean distance, Threshold, Non-contact

CLC Number: 

  • TP391
[1]POH M Z,MCDUFF D J,PICARD R W,et al.Non-contact,automated cardiac pulse measurements using video imaging and blind source separation[J].Optics Express,2010,18(10):10762-10774.
[2]POH M Z,MCDUFF D J,PICARD R W.Advancements in noncontact,multiparameter physiological measurements using a webcam[J].IEEE Transactions on Biomedical Engineering,2010,58(1):7-11.
[3]WANG Y D,LI F H.Non-Contact Heart Rate Detection ofMulti-Feature Area Fast ICA[J].Computer Systems & Applications,2021,30(1):154-161.
[4]CHEN H,ZHENG X J,NI Z J.Vital Signs Detection Based on Facial Video Analysis[J].Journal of Beijing University of Aeronautics and Astronautics,2020,46(9):1770-1777.
[5]CUMO S,DE G,FARINA R,et al.A novel on numerical scheme for ECG signal denoising[J].Procedia Computer Science,2015,51(1):775-784.
[6]MOEIN S.An MLP neural network for ECG noise removalbased on Kalman filter[J].Oxygen Transport to Tissue XXXIII,2010,680(680):109-116.
[7]SMITAL L,VITEK M,KOZUMPLIK J,et al.Adaptive wavelet wiener filtering of ECG signals[J].IEEE Transactions on Biomedical Engineering,2013,60(2):437-445.
[8]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings Mathematical Physical & Engineering Sciences,1998,454(1971):903-995.
[9]NGUYEN P,KIM J M.Adaptive ECG denoising using genetic algorithm-based thresholding and ensemble empirical mode decomposition[J].Information Sciences,2016,373(C):499-511.
[10]MOHGUEN W,BEKKA R E.EMD-Based Denoising by Customized Thresholding[C]//International Conference on Control,2017:19-23.
[11]LING L Y,WANG Q Q,ZHOU M R.Non-Contact Measurement of Heart Rate Based on CEEMDAN-FastICA[J].Journal of Anhui University of Science and Technology(Natural Science Edition),2021,41(2):1-8.
[12]WU T,BLAZEK V,SCHMITT H J.Photoplethysmography Imaging:A New Noninvasive and Noncontact Method for Mapping of the Dermal Perfusion Changes[C]//European Confe-rence on Biomedical Optics.2000.
[13]BOUDRAA A O,CEXUS J C,SAIDI Z.EMD-based signal noise reduction[J].International Journal of Signal Processing,2004,1(1):33-37.
[14]TANG J T,ZOU Q,YAN T,et al.Hilbert-Huang Transform for ECG De-Noising[C]//International Conference on Bioinformatics & Biomedical Engineering.2007.
[15]LIU Y,OUYANG J F,YAN Y G.Method of Measuring Heart Rate Using A Webcam[J].Computer Engineering and Applications,2016,52(7):210-214.
[16]QI G,YANG X Z,WU X.Heart Rate Detection for Non-coope-rative Shaking Face[J].Journal of Image and Graphics,2017,22(1):126-136.
[17]SANG H F,JIN Z Y.Face Local Heart Rate Detection Based on Illumination Correction [J].Journal of Computer Applications,2018,38(S2):301-305.
[18]LI C X,ZHONG Q H,LIAO J X.Heart Rate Measurementfrom Face Video Based on ICEEMD[J].Laser Journal,2019,40(1):33-36.
[19]SU P Q,XU L,LIANG Y J.Non-Contact Heart Rate Measurement Method Based on Eulerian Video Magnification[J].Journal of Computer Applications,2018,38(3):916-922.
[20]WU Z,HUANG N E.Ensemble empirical mode decomposition:a noise-assisted data analysis method [J].Advances in Adaptive Data Analysis,2011,1(1):1-41.
[21]CENNINI G,ARGUEL J,AKIT K,et al.Heart rate monitoring via remote photoplethysmography with motion artifacts reduction[J].Optics Express,2010,18(5):4867-4875.
[22]SHIMAZAKI T,HARA S,OKUHATA H,et al.Cancellation of motion artifact induced by exercise for PPG-based heart rate sensing[C]//2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.IEEE,2014:3216-3219.
[23]FLANDTIN P,GONCALVES P,RILLING G.EMD equivalent filter banks,from interpretation to applications[M].Hilbert-Huang Transformand Its Applications,2011.
[24]TERRIENE J,MARQUE C,KARLSSON B.Automatic detec-tion of mode mixing in empirical mode decomposition using non-stationarity detection:application to selecting IMFs of interest and denoising[J].EURASIP Journal on Advances in Signal Processing,2011,2011(1):1-8.
[25]XU Z J,GAO G Q,FANG Z M.Non-Contact Infant Heart Rate Monitoring Based on Facial Images[J].Software Guide,2019,18(10):12-18.
[26]HUANG B H,CHEN R,ZENG H S,et al.The impact of blood content in skin tissue on skin spectra[J].Guang pu xue yu Guang pu fen xi= Guang pu,2007,27(1): 95-98.
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