Why the study?
Skin tone, body movement, exercise recovery, and variable or inadequate illumination limit the accuracy and robustness of rPPG-based heart rate measurement.
Does a rPPG-based HR measurement method combining JBSS and a skin reflection model improve the accuracy and robustness of heart rate measurement compared to state-of-the-art methods in subjects with different skin tones under various environmental scenarios?
Does a rPPG-based HR measurement method combining JBSS and a skin reflection model improve the accuracy and robustness of heart rate measurement compared to state-of-the-art methods in subjects with different skin tones under various environmental scenarios?
A novel webcam-based rPPG method combining JBSS and a skin reflection model improves noncontact heart rate measurement accuracy across diverse skin tones and lighting conditions.
Supports expanded testing of webcam rPPG across skin tones; leaves open clinical outcome validation.
Remote photoplethysmography (rPPG) can be used for noncontact and continuous measurement of the heart rate (HR). Currently, the main factors affecting the accuracy and robustness of rPPG‐based HR measurement methods are the subject’s skin tone, body movement, exercise recovery, and variable or inadequate illumination. In response to these challenges, this study is aimed at investigating a rPPG‐based HR measurement method that is effective under a wide range of conditions by only using a webcam. We propose a new approach, which combines joint blind source separation (JBSS) and a projection process based on a skin reflection model, so as to eliminate the interference of background illumination and enhance the extraction of pulse rate information. Three datasets derived from subjects with different skin tones considering six environmental scenarios are used to validate the proposed method against three other state‐of‐the‐art methods. The results show that the proposed method can provide more accurate and robust HR measurement for all three datasets and is therefore more applicable to a wide range of scenarios.
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Zhang et al. (2021) studied this question.
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