Algorithmic principles of remote PPG
Open accessAbstract
This paper introduces a mathematical model that incorporates the pertinent optical and physiological properties of skin reflections with the objective to increase our understanding of the algorithmic principles behind remote photoplethysmography (rPPG). The model is used to explain the different choices that were made in existing rPPG methods for pulse extraction. The understanding that comes from the model can be used to design robust or application-specific rPPG solutions. We illustrate this by designing an alternative rPPG method, where a projection plane orthogonal to the skin tone is used for pulse extraction. A large benchmark on the various discussed rPPG methods shows that their relative merits can indeed be understood from the proposed model.
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Numerous other studies that stratify results against Fitzpatrick classification identify the same trend: errors in determining heart rate from wearable PPG devices that use primarily green light are increased in individuals with dark skin tones due to high absorption caused by increased amounts of epidermal melanin.
“In addition to these examples, numerous other studies that stratify results against Fitzpatrick classification identify the same trend; errors in determining heartrate from wearable PPG devices that use primarily green light as their source is increased in individuals with dark skin tones due to the high absorption caused by increased amounts of epidermal melanin [42,43,44,45].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [42]
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“For a thorough evaluation, we benchmark it with seven commonly used or state-of-the-art rPPG methods: 1) G (2007) [1], the single wavelength method that is still popular as evidenced by recent researches [7], [10].”
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“Also, we include some traditional methods such as POS [60] and CHROM [12] as baseline results.”
Method
- Authors
- Wang, W., den Brinker, A. C., Stuijk, S., & de Haan, G.
- Affiliations
- Eindhoven University of Technology (NL)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2017-07
- Volume
- 64
- Issue
- 7
- Pages
- 1479-1491
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2520509592
- Cited by
- 1,234
- References
- 21
- Citations by year
- 2026: 141 · 2025: 220 · 2024: 203 · 2023: 187 · 2022: 150 · 2021: 128 · 2020: 76 · 2019: 66 · 2018: 43 · 2017: 20
- FWCI
- 20.73
- Type
- journal article
- Language
- en
- Open access
- green
- research.tue.nl
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- TU/e Research Portal (submittedVersion)
- TU/e Research Portal (submittedVersion, other-oa)
- Funders
- Technische Universiteit Eindhoven
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- remote photoplethysmography, pulse extraction, projection plane, skin tone
- MeSH terms
- Algorithms, Blood Flow Velocity, Blood Volume, Blood Volume Determination, Colorimetry, Computer Simulation, Humans, Image Interpretation, Computer-Assisted, Light, Models, Biological, Photography, Scattering, Radiation, Sensitivity and Specificity, Skin Physiological Phenomena, Reproducibility of Results, Photoplethysmography, Monitoring, Ambulatory, Remote Sensing Technology
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