Paper

Abstract

Objective. Remote photoplethysmography (rPPG) offers a promising method for contactless pulse rate monitoring, which is particularly valuable for remote patient care. However, signal noise—caused by factors such as motion and lighting—can significantly impact measurement accuracy. Approach. We present a hybrid algorithm that combines frequency-domain analysis to estimate initial pulse rate and a time-domain approach to refine this estimate, improving robustness in challenging conditions. Main Results. The combined method increases accuracy and success rate compared to time-domain methods alone. Evaluated against time-aligned ECG, it achieved a root mean square error (RMSE) as low as 2.0 bpm and an r2 of 0.96. On a larger outpatient dataset, the RMSE was 3.2 bpm with an r2 of 0.93. Importantly, no significant performance difference was observed across varying skin tones. Significance These results demonstrate that the proposed PR algorithm enables reliable, contactless pulse monitoring in real-world conditions, supporting broader adoption of rPPG for inclusive and scalable remote health monitoring.

Authors: Lieke Dorine van Putten, Ayman Ahmed and Simon Christopher Wegerif

Source: https://iopscience.iop.org/article/10.1088/1361-6579/ae1804