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Real-time realizable mobile imaging photoplethysmographyopen access

Authors
Lee, HooseokKo, HoonChung, HeewonNam, YunyoungHong, SangjinLee, Jinseok
Issue Date
May-2022
Publisher
Nature Publishing Group
Citation
Scientific Reports, v.12, no.1, pp 1 - 14
Pages
14
Journal Title
Scientific Reports
Volume
12
Number
1
Start Page
1
End Page
14
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/20746
DOI
10.1038/s41598-022-11265-x
ISSN
2045-2322
Abstract
Photoplethysmography imaging (PPGI) sensors have attracted a significant amount of attention as they enable the remote monitoring of heart rates (HRs) and thus do not require any additional devices to be worn on fingers or wrists. In this study, we mounted PPGI sensors on a robot for active and autonomous HR (R-AAH) estimation. We proposed an algorithm that provides accurate HR estimation, which can be performed in real time using vision and robot manipulation algorithms. By simplifying the extraction of facial skin images using saturation (S) values in the HSV color space, and selecting pixels based on the most frequent S value within the face image, we achieved a reliable HR assessment. The results of the proposed algorithm using the R-AAH method were evaluated by rigorous comparison with the results of existing algorithms on the UBFC-RPPG dataset (n = 42). The proposed algorithm yielded an average absolute error (AAE) of 0.71 beats per minute (bpm). The developed algorithm is simple, with a processing time of less than 1 s (275 ms for an 8-s window). The algorithm was further validated on our own dataset (BAMI-RPPG dataset [n = 14]) with an AAE of 0.82 bpm.
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