Heart rate measurement based on face video sequence

This paper proposes a new non-contact heart rate measurement method based on photoplethysmography (PPG) theory. With this method we can measure heart rate remotely with a camera and ambient light. We collected video sequences of subjects, and detected remote PPG signals through video sequences. Remote PPG signals were analyzed with two methods, Blind Source Separation Technology (BSST) and Cross Spectral Power Technology (CSPT). BSST is a commonly used method, and CSPT is used for the first time in the study of remote PPG signals in this paper. Both of the methods can acquire heart rate, but compared with BSST, CSPT has clearer physical meaning, and the computational complexity of CSPT is lower than that of BSST. Our work shows that heart rates detected by CSPT method have good consistency with the heart rates measured by a finger clip oximeter. With good accuracy and low computational complexity, the CSPT method has a good prospect for the application in the field of home medical devices and mobile health devices.

[1]  L. O. Svaasand,et al.  Remote plethysmographic imaging using ambient light. , 2008, Optics express.

[2]  Tomasz Kocejko,et al.  Proceedings of the Federated Conference on Computer Science and Information Systems pp. 405–410 ISBN 978-83-60810-22-4 Measuring Pulse Rate with a Webcam – a Non-contact Method for Evaluating Cardiac Activity , 2022 .

[3]  Ted Weatherred,et al.  Significance of heart rate variability in cardiovascular disease , 1995 .

[4]  L. Tarassenko,et al.  Non-contact video-based vital sign monitoring using ambient light and auto-regressive models , 2014, Physiological measurement.

[5]  F. Mastik,et al.  Contactless Multiple Wavelength Photoplethysmographic Imaging: A First Step Toward “SpO2 Camera” Technology , 2005, Annals of Biomedical Engineering.

[6]  T. Ward,et al.  Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry. , 2007, The Review of scientific instruments.

[7]  Rosalind W. Picard,et al.  Non-contact, automated cardiac pulse measurements using video imaging and blind source separation , 2022 .

[8]  Yu Sun,et al.  Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise. , 2011, Journal of biomedical optics.

[9]  C. Takano,et al.  Heart rate measurement based on a time-lapse image. , 2007, Medical engineering & physics.

[10]  Luping Fang,et al.  [A new method of measuring the pulse based on facial video]. , 2012, Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi.

[11]  Frédéric Bousefsaf,et al.  Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate , 2013, Biomed. Signal Process. Control..

[12]  Daniel McDuff,et al.  Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam , 2011, IEEE Transactions on Biomedical Engineering.

[13]  Qi Mei-bin.  Real-time algorithm for face tracking based on mean-shift , 2008 .