The Impact of Video Compression on Remote Cardiac Pulse Measurement Using Imaging Photoplethysmography

Remote physiological measurement has great potential in healthcare and affective computing applications. Imaging photoplethysmography (iPPG) leverages digital cameras to recover the blood volume pulse from the human body. While the impact of video parameters such as resolution and frame rate on iPPG accuracy have been studied, there has not been a systematic analysis of video compression algorithms. We compared a set of commonly used video compression algorithms (x264 and x265) and varied the Constant Rate Factor (CRF) to measure pulse rate recovery for a range of bit rates (file sizes) and video qualities. We found that compression, even at a low CRF, degrades the blood volume pulse (BVP) signal-tonoise ratio considerably. However, the bit rate of a video can be substantially decreased (by a factor of over 1000) without destroying the BVP signal entirely. We found an approximately linear relationship between bit rate and BVP signal-to-noise ratio up to a CRF of 36. A faster decrease in SNR was observed for videos of the task involving larger head motions and the x265 algorithm appeared to work more effectively in these cases.

[1]  Daniel McDuff,et al.  Improvements in Remote Cardiopulmonary Measurement Using a Five Band Digital Camera , 2014, IEEE Transactions on Biomedical Engineering.

[2]  Westgate Road,et al.  Photoplethysmography and its application in clinical physiological measurement , 2007 .

[3]  Sander Stuijk,et al.  Exploiting Spatial Redundancy of Image Sensor for Motion Robust rPPG , 2015, IEEE Transactions on Biomedical Engineering.

[4]  Gary J. Sullivan,et al.  Overview of the High Efficiency Video Coding (HEVC) Standard , 2012, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Daniel McDuff,et al.  A survey of remote optical photoplethysmographic imaging methods , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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

[7]  Ethan B. Blackford,et al.  Recovering pulse rate during motion artifact with a multi-imager array for non-contact imaging photoplethysmography , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[8]  Yu Sun,et al.  Use of ambient light in remote photoplethysmographic systems: comparison between a high-performance camera and a low-cost webcam. , 2012, Journal of biomedical optics.

[9]  Giovanni Cennini,et al.  Heart rate monitoring via remote photoplethysmography with motion artifacts reduction. , 2010, Optics express.

[10]  Yuting Yang,et al.  Noncontact Monitoring Breathing Pattern, Exhalation Flow Rate and Pulse Transit Time , 2014, IEEE Transactions on Biomedical Engineering.

[11]  Mika P. Tarvainen,et al.  An advanced detrending method with application to HRV analysis , 2002, IEEE Transactions on Biomedical Engineering.

[12]  Sander Stuijk,et al.  Motion Robust Remote-PPG in Infrared , 2015, IEEE Transactions on Biomedical Engineering.

[13]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[14]  Anne Aaron,et al.  A large-scale video codec comparison of x264, x265 and libvpx for practical VOD applications , 2016, Optical Engineering + Applications.

[15]  David A. Clausi,et al.  High-resolution motion-compensated imaging photoplethysmography for remote heart rate monitoring , 2015, Photonics West - Biomedical Optics.

[16]  Jean-François Cardoso,et al.  Multidimensional independent component analysis , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[17]  Ethan B. Blackford,et al.  Effects of frame rate and image resolution on pulse rate measured using multiple camera imaging photoplethysmography , 2015, Medical Imaging.

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

[19]  J. Astola,et al.  ON BETWEEN-COEFFICIENT CONTRAST MASKING OF DCT BASIS FUNCTIONS , 2007 .

[20]  Gerard de Haan,et al.  Robust Pulse Rate From Chrominance-Based rPPG , 2013, IEEE Transactions on Biomedical Engineering.

[21]  T. Fitzpatrick.  The validity and practicality of sun-reactive skin types I through VI. , 1988, Archives of dermatology.

[22]  Itu-T and Iso Iec Jtc.  Advanced video coding for generic audiovisual services , 2010 .

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

[24]  D. Haan,et al.  Improved motion robustness of remote-PPG by using the blood volume pulse signature , 2014 .

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

[26]  Lionel Tarassenko,et al.  Non-contact measurement of oxygen saturation with an RGB camera. , 2015, Biomedical optics express.