Remote photoplethysmography for contactless pulse rate monitoring: algorithm development and accuracy assessment

Objective.Remote photoplethysmography (rPPG) offers a promising method for contactless pulse rate (PR) 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 PR 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 electrocardiogram, it achieved a root mean square error (RMSE) as low as 2.0 bpm and anr²of 0.96. On a larger outpatient dataset, the RMSE was 3.2 bpm with anr²of 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.