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

<i>Objective.</i>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.<i>Approach.</i>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.<i>Main results.</i>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 an<i>r</i><sup>2</sup>of 0.96. On a larger outpatient dataset, the RMSE was 3.2 bpm with an<i>r</i><sup>2</sup>of 0.93. Importantly, no significant performance difference was observed across varying skin tones.<i>Significance.</i>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.

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Publication Details

Journal
Physiological Measurement
Published
2025-10-27
DOI
https://doi.org/10.1088/1361-6579/ae1804
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.67
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article

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

Lieke Dorine van Putten, Ayman Ahmed, Simon Wegerif
1 citations
Physiological Measurement
Non-Invasive Vital Sign Monitoring
0.67
article

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

Lieke Dorine van Putten, Ayman Ahmed, Simon Wegerif
article en
1 citations

Abstract

<i>Objective.</i>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.<i>Approach.</i>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.<i>Main results.</i>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 an<i>r</i><sup>2</sup>of 0.96. On a larger outpatient dataset, the RMSE was 3.2 bpm with an<i>r</i><sup>2</sup>of 0.93. Importantly, no significant performance difference was observed across varying skin tones.<i>Significance.</i>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.

Physiological MeasurementVol. 46(11)
Chilworth Technology (United Kingdom) (GB), University of Southampton (GB)
Openalex Percentile: Top 25%
Non-Invasive Vital Sign Monitoring
0.67
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Remote photoplethysmography for contactless pulse rate monitoring: algorithm development and accuracy assessment — Lieke Dorine van Putten, Ayman Ahmed, et al. · Physiological Measurement (2025) | TGRS Research Map | TGRS