Demographic bias in public remote photoplethysmography datasets.
systematic_review · Level I
Where this comes from
- Record sourced from PubMed, PMID 41038972.
- Also identified by DOI 10.1038/s41746-025-01973-9 and PMC identifier 12491395.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Remote photoplethysmography (rPPG) is gaining traction for non-contact heart rate estimation, yet most publicly available datasets are demographically biased. In this study, we analyze 100 rPPG studies, providing the first quantitative cross-model audit of demographic bias in rPPG and demonstrating significant underrepresentation of darker skin tones and gender imbalance. Our findings reveal how this bias limits model fairness and accuracy and propose steps to improve dataset inclusivity and algorithmic robustness.