ArticleNPJ digital medicine2025
Demographic bias in public remote photoplethysmography datasets.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- When is rPPG physiologically valid for stress and workload monitoring? A PRISMA-ScR scoping review.Frontiers in digital health · 2026Pooled it
- Rationale and design of the AutoHealth study: prospective clinical validation of continuous multimodal in-vehicle health monitoring in real-world mobility.European heart journal. Digital health · 2026Article
- Missed isochromatic cardiac pulsation in remote photoplethysmography: detection, impact, and removal.Biomedical optics express · 2026Article
- Roadmap of remote photoplethysmography from heart rate measurement toward clinical translation.NPJ digital medicine · 2026Article
- Combining Video Magnification with Machine Learning-Based Source Identification for Contactless Heart Rate Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Adaptive physiology-informed correction for reliable remote photoplethysmography heart-rate monitoring.NPJ digital medicine · 2026Article
- DeepRespNet: a hybrid attention-recurrent framework for non-contact respiratory rate estimation.Frontiers in physiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.