Camera-Based Physiological Sensing: Challenges and Future Directions
- URL: http://arxiv.org/abs/2110.13362v1
- Date: Tue, 26 Oct 2021 02:30:18 GMT
- Title: Camera-Based Physiological Sensing: Challenges and Future Directions
- Authors: Xin Liu, Shwetak Patel, Daniel McDuff
- Abstract summary: We identify four research challenges for the field of camera-based physiological sensing and broader AI driven healthcare communities.
We believe solving these challenges will help deliver accurate, equitable and generalizable AI systems for healthcare.
- Score: 5.571184025017747
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Numerous real-world applications have been driven by the recent algorithmic
advancement of artificial intelligence (AI). Healthcare is no exception and AI
technologies have great potential to revolutionize the industry. Non-contact
camera-based physiological sensing, including remote photoplethysmography
(rPPG), is a set of imaging methods that leverages ordinary RGB cameras (e.g.,
webcam or smartphone camera) to capture subtle changes in electromagnetic
radiation (e.g., light) reflected by the body caused by physiological
processes. Because of the relative ubiquity of cameras, these methods not only
have the ability to measure the signals without contact with the body but also
have the opportunity to capture multimodal information (e.g., facial
expressions, activities and other context) from the same sensor. However,
developing accessible, equitable and useful camera-based physiological sensing
systems comes with various challenges. In this article, we identify four
research challenges for the field of camera-based physiological sensing and
broader AI driven healthcare communities and suggest future directions to
tackle these. We believe solving these challenges will help deliver accurate,
equitable and generalizable AI systems for healthcare that are practical in
real-world and clinical contexts.
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