Computer vision-based methods for noncontact vital sign measurement require further research in noise removal, multi-person monitoring, and multi-camera fusion for real-world applications.
Computer vision systems offer a promising noncontact approach for vital sign monitoring, though significant technical challenges remain before widespread real-world application.
Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be robust, hygienic, reliable, safe, cost effective and suitable for long distance and long-term monitoring. In addition, video techniques allow measurements from multiple individuals opportunistically and simultaneously in groups. This paper aims to explore the progress of the technology from controlled clinical scenarios with fixed monitoring installations and controlled lighting, towards uncontrolled environments, crowds and moving sensor platforms. We focus on the diversity of applications and scenarios being studied in this topic. From this review it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.
Khanam et al. (Tue,) reported a review. Computer vision-based methods for noncontact measurement of vital signs was evaluated. Computer vision-based methods for noncontact vital sign measurement require further research in noise removal, multi-person monitoring, and multi-camera fusion for real-world applications.
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