ArticleNPJ digital medicine2026
Adaptive physiology-informed correction for reliable remote photoplethysmography heart-rate monitoring.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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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.
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Who cites it
1 citing paper in PubMed.
- Lighting effects on optimal facial regions for remote heart rate measurement.NPJ cardiovascular health · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Contactless heart rate (HR) monitoring demonstrates significant potential for mobile health and telemedicine, but current remote photoplethysmography (rPPG) approaches remain vulnerable to various noise sources. While existing research has emphasized signal-level enhancement, correcting erroneous HR estimates remains underexplored. We present a plug-and-play adaptive correction algorithm that leverages cardiac dynamics constraints, adjusting HR estimates based on physiological priors of HR elevation and recovery. By mapping HR frequencies to indices and applying adaptive corrections, our method significantly reduces measurement errors with minimal computational load, even under challenging conditions. Across three public datasets, the algorithm increased the proportion of accurate measurements (mean absolute error ≤ 10 beats per minute) from 46.26% to 84.14% (LGI-PPGI), 48.03% to 69.21% (BUAA-MIHR), and 92.22% to 96.67% (UBFC-rPPG), outperforming existing correction techniques. The lightweight design facilitates seamless edge-side integration, providing a scalable solution for enhancing the reliability of contactless HR monitoring in mobile and remote healthcare settings.
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Registered trials
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