ArticleFrontiers in physiology2023
Evaluating RGB channels in remote photoplethysmography: a comparative study with contact-based PPG.
Article in Frontiers in physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Roadmap of remote photoplethysmography from heart rate measurement toward clinical translation.NPJ digital medicine · 2026Article
- Advancing remote photoplethysmography (rPPG) to facilitate cardiac monitoring in naturalistic settings using webcam technology.Behavior research methods · 2026Article
- Reliability of contactless vital sign measurement algorithms for use in drone-based mass casualty triage.Scientific reports · 2026Article
- Adaptive physiology-informed correction for reliable remote photoplethysmography heart-rate monitoring.NPJ digital medicine · 2026Article
- Balancing cardiac privacy with quality in video recordings.Communications medicine · 2025Article
- The role of face regions in remote photoplethysmography for contactless heart rate monitoring.NPJ digital medicine · 2025Article
- Hyperspectral reconstruction for mobile diabetic foot blood perfusion monitoring.BMC artificial intelligence · 2025Article
- Observation of blood motion in the internal jugular vein by contact and contactless photoplethysmography during physiological testing: case studies.Biomedical optics express · 2024Article
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Authors and funding
4 authors.
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Abstract
Remote photoplethysmography (rPPG) provides a non-contact method for measuring blood volume changes. In this study, we compared rPPG signals obtained from video cameras with traditional contact-based photoplethysmography (cPPG) to assess the effectiveness of different RGB channels in cardiac signal extraction. Our objective was to determine the most effective RGB channel for detecting blood volume changes and estimating heart rate. We employed dynamic time warping, Pearson's correlation coefficient, root-mean-square error, and Beats-per-minute Difference to evaluate the performance of each RGB channel relative to cPPG. The results revealed that the green channel was superior, outperforming the blue and red channels in detecting volumetric changes and accurately estimating heart rate across various activities. We also observed that the reliability of RGB signals varied based on recording conditions and subject activity. This finding underscores the importance of understanding the performance nuances of RGB inputs, crucial for constructing rPPG signals in algorithms. Our study is significant in advancing rPPG research, offering insights that could benefit clinical applications by improving non-contact methods for blood volume assessment.
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