학술논문

Full-Body Cardiovascular Sensing with Remote Photoplethysmography
Document Type
Conference
Source
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 IEEE/CVF Conference on. :5994-6004 Jun, 2023
Subject
Computing and Processing
Engineering Profession
Legged locomotion
Heart rate
Face recognition
Estimation
Photoplethysmography
Cameras
Monitoring
Language
ISSN
2160-7516
Abstract
Remote photoplethysmography (rPPG) allows for non-contact monitoring of blood volume changes from a camera by detecting minor fluctuations in reflected light. Prior applications of rPPG focused on face videos. In this paper we explored the feasibility of rPPG from non-face body regions such as the arms, legs, and hands. We collected a new dataset titled Multi-Site Physiological Monitoring (MSPM), which will be released with this paper. The dataset consists of 90 frames per second video of exposed arms, legs, and face, along with 10 synchronized PPG recordings. We performed baseline heart rate estimation experiments from non-face regions with several state-of-the-art rPPG approaches, including chrominance-based (CHROM), plane-orthogonal-to-skin (POS) and RemotePulseNet (RPNet). To our knowledge, this is the first evaluation of the fidelity of rPPG signals simultaneously obtained from multiple regions of a human body. Our experiments showed that skin pixels from arms, legs, and hands are all potential sources of the blood volume pulse. The best-performing approach, POS, achieved a mean absolute error peaking at 7.11 beats per minute from non-facial body parts compared to 1.38 beats per minute from the face. Additionally, we performed experiments on pulse transit time (PTT) from both the contact PPG and rPPG signals. We found that remote PTT is possible with moderately high frame rate video when distal locations on the body are visible. These findings and the supporting dataset should facilitate new research on non-face rPPG and monitoring blood flow dynamics over the whole body with a camera.