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

Remote physiological measurement technique leverages digital cameras to recover the blood volume pulse from the human body

Remote measurement of physiological signals has a number of advantages over traditional contact methods. It allows the measurement of vital signals unobtrusively and concomitantly. In recent years, a number of approaches for imaging-based measurement of physiology using digital cameras have been proposed. Imaging photoplethysmography (iPPG) captures variations in light reflected from the body due to blood volume changes in microvascular tissue. It has been demonstrated that sub-pixel variations in color channel measurements from a digital single lens reflex (DSLR) camera, when aggregated, could be used to recover the blood volume pulse. Subsequently, it was shown that iPPG methods can allow accurate measurement of heart rate, heart rate variability, breathing rate, blood oxygenation and pulse transit time.

A systematic analysis of the impact of video compression on physiological measurements via imaging photoplethysmography. Compression types and levels on over four hours of video from twenty-five participants performing stationary and random head motion tasks were compared.

A number of parameters influence the accuracy of iPPG measurements. These include the imager quality, and the frame rate and resolution of the images. Previous research compared remote physiological measurement using a low cost webcam and a high-speed color CMOS and showed similar signals were captured from both cameras, further supporting that iPPG is a practical method for scalable applications such as telemedicine. It was also found that reducing frame rate from 120Hz to 30Hz and/or reducing image resolution from 658×492 pixels to 329×246 pixels had little impact on the accuracy of pulse rate measurements. Video compression is an important parameter that has not been systematically studied with regard to iPPG.

There are a number of methods for video compression that aim to reduce the bit rate while retaining the important visual information within a video. However, video compression algorithms are not designed with the intention of preserving photoplethysmographic data. On the contrary compression algorithms often make assumptions that small changes in pixel values between frames are not of high visual importance and discard them, influencing the underlying variations on which iPPG methods rely. This research presents a comparison of iPPG blood volume pulse (BVP) signal- to-noise ratios and pulse rate (PR) measurements from videos compressed using popular current and next-generation codecs (×264 and ×265).

In real-life applications, motion tolerance of iPPG measurement is likely to be important. Previous work has proposed methods for reducing motion artifacts in iPPG measurements. Due to the nature of inter-frame compression, compression is likely to have different impacts on physiological signal recovery depending on the level of head motion. Therefore, results on videos for stationary and motion tasks were evaluated.

Finding compression configurations that preserve valuable physiological data would allow new applications for iPPG measurement. For example, methods used for video recording/streaming through a web browser in video conferencing could be adapted to preserve iPPG data for analysis as part of a telehealth system. Additionally, alleviating the burden of storing raw video could enable sharing research datasets. A large dataset of uncompressed, raw videos with both stationary subjects and random head motions was analyzed in order to test the impact of video compression on the accuracy of remote physiological measurements. Participants (n=25) engaged in two, 5-minute tasks and were recorded using an array of cameras. Gold-standard electrocardiogram (ECG) measurements were captured alongside contact PPG measurements from the fingertip. A summary of this study and examples of frames from the two tasks are shown in the accompanying figure.

This work was done by Daniel McDuff, Microsoft Research; Ethan B. Blackford, Ball Aerospace; and Justin R. Estepp for the Air Force Research Laboratory. AFRL-0256

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

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