Illumination variation-resistant video-based heart rate measurement using recursive least squares and complete ensemble empirical mode decomposition with adaptive noise

Jingwei Xu; Chao Zhang; Zhao Lv

doi:10.1117/12.3022956

28 March 2024 Illumination variation-resistant video-based heart rate measurement using recursive least squares and complete ensemble empirical mode decomposition with adaptive noise

Jingwei Xu, Chao Zhang, Zhao Lv

Author Affiliations +

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130910Q (2024) https://doi.org/10.1117/12.3022956
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

Heart rate is closely related to physiological and psychological states, and video-based techniques such as Imaging Photoplethysmography (IPPG) have been developed for heart rate detection. Although there have been some methods based on IPPG that are used to address the impact of illumination changes on heart rate detection, these methods perform poorly in environments with intense or complex illumination. This study proposes a framework that uses normalized least mean square adaptive filtering and singular spectrum analysis to combat the effects of illumination changes on heart rate detection. Experimental results on a dataset comprising 13 men and women aged 20 to 28 demonstrate the feasibility of our method under illumination changes.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingwei Xu, Chao Zhang, and Zhao Lv "Illumination variation-resistant video-based heart rate measurement using recursive least squares and complete ensemble empirical mode decomposition with adaptive noise", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130910Q (28 March 2024); https://doi.org/10.1117/12.3022956

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