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A Comprehensive Review of rPPG Methods for Heart Rate Estimation

DOI: 10.4236/oalib.1112482, PP. 1-19

Subject Areas: Artificial Intelligence, Image Processing

Keywords: Remote Photoplethysmography (rPPG), Heart Rate Measurement, Remote Health Monitoring, Computer Vision, Deep Learning

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Abstract

Recently, there has been an increasing interest in assessing basic health indications covering blood pressure, heartbeat, and breathing rate using remote photoplethysmography (rPPG) to obtain the results without direct contact with humans; rPPG has become essential to measuring vital signs while avoiding difficulties in many cases, such as transmission of infection through contact with persons who have serious diseases or disturbing people with sensitive skin or newborn babies. This technique can also be used for other applications, such as monitoring people’s stress levels during indirect investigations and monitoring the health indications of truck drivers to send them a notification if they suffer a health crisis. This paper discusses the methods used in remote photoplethysmography (rPPG) that focus on measuring the photoplethysmography (PPG) using an RGB camera. These techniques achieved good results corresponding to the availability, cost, and ease of use.

Cite this paper

Salim, A. S. and Khidhir, A. S. M. (2024). A Comprehensive Review of rPPG Methods for Heart Rate Estimation. Open Access Library Journal, 11, e2482. doi: http://dx.doi.org/10.4236/oalib.1112482.

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