A Review of Methods for Non-Invasive Heart Rate Measurement on Wrist
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Algorithm developmental biases stem from selecting features, adjusting training data composition, and model calibrations.
“The accuracy of heart rate measurements affects people with darker skin tones because of algorithm developmental biases that stem from selecting features and adjusting training data composition and model calibrations [23-26].”
From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [25]
Cites
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An Ultra Low Power Personalizable Wrist Worn ECG Monitor Integrated With IoT Infrastructure
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Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring
Asif, S., AlSaafeen, A., Nadar, S., Nambiar, S., Dannawi, J., Korrapati, H., & Wilkhoo, H. S. (2025) · Cureus · doi:10.7759/cureus.94074 · Cited by 9 · see citing works
- Authors
- De Pinho Ferreira, N., Gehin, C., & Massot, B.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- ORCID
- Massot, B.
- Venue
- IRBM
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 42
- Issue
- 1
- Pages
- 4-18
- ISSN
- 1876-0988 (ISSN-L)
- 1959-0318
- OpenAlex
- W3020616984
- Cited by
- 49
- References
- 12
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 10 · 2023: 8 · 2022: 10 · 2021: 5
- FWCI
- 1.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- IRBM (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- heart rate measurement, wrist-worn devices, wearable sensors, ambulatory monitoring, motion artifacts, artifact reduction, wearable activity trackers, heart disease diagnosis
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