Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Güler, Saygun and Jedari Golparvar, Ata and Öztürk, Özberk and Dogan, Huseyin and Yapıcı, Murat Kaya (2023) Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning. Biomedical Physics and Engineering Express, 9 (2). ISSN 2057-1976

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Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still not straightforward. The best algorithm selection improves the signal-to-noise ratio (SNR) and therefore improves the accuracy of the recognition and classification of vital signs. We recorded more than 300 temporal rPPG signals where the noise was not motion-induced. Then, we investigated the best digital filter in pre-processing temporal rPPG data and compared the performances of 10 filters with 10 orders each (i.e., a total of 100 filters). The performances are assessed using a signal quality metric on three levels. The quality of the raw signals was classified under three categories; Q1 being the best and Q3 being the worst. The results are presented in SNR scores, which show that the Chebyshev II orders of 2nd, 4th, and 6th perform the best for denoising rPPG signals.
Item Type: Article
Uncontrolled Keywords: digital signal processing; health monitoring; heart rate; human-computer interaction; image processing; photoplehysmography; vital signs
Divisions: Faculty of Engineering and Natural Sciences
Sabancı University Nanotechnology Research and Application Center
Depositing User: Saygun Güler
Date Deposited: 14 Apr 2023 15:20
Last Modified: 05 Oct 2023 14:49
URI: https://research.sabanciuniv.edu/id/eprint/45365

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