Imaging Photoplethysmography: What are the Best Locations on the Face to Estimate Heart Rate?
Open accessAbstract
The potential of imaging photoplethysmography for cardiovascular monitoring applications has been demonstrated recently.Various processing schemes have been proposed to extract heart rate (HR) from a defined region of interest (ROI) on the face.However, the reasons that motivate the choice of the ROI are often unclear.This study aimed at investigating the spatial distribution of the HR-related information on the subject face, based on a partition into 260 small ROIs.A power spectral density (PSD) analysis was performed to determine the amount of HR-related information in each ROI.Normalized color maps were used to visualize the spatial distribution of the HR-information and clearly showed that color fluctuations due to blood volume changes are always more pronounced in the forehead region.After face segmentation, for the R/G/B/NIR channels, average percentages of power of 27%/43%/27%/36% for the forehead region, 17%/28%/18%/21% for the cheek region and 16%/24%/16%/20% for the whole face were obtained.
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For all wavelengths of light, the forehead is superior to the cheeks and the whole face for determining heart rate.
“Fallet et al. found via iPPG that for all wavelengths of light, the forehead is superior to the cheeks and the whole face for determining heart rate.”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [146]
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Verkruysse, W., Svaasand, L. O., & Nelson, J. S. (2008) · Optics Express · doi:10.1364/oe.16.021434 · Cited by 1,728 · see citing works
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Signal recovery in imaging photoplethysmography
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Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
Fine, J., Branan, K. L., Rodriguez, A. J., Boonya-ananta, T., Ajmal, Ramella-Roman, J. C., McShane, M. J., & Coté, G. L. (2021) · Biosensors · doi:10.3390/bios11040126 · Cited by 348 · see citing works
- Authors
- Fallet, S., Moser, V., Braun, F., & Vesin, J.-M.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Swiss Center for Electronics and Microtechnology (Switzerland) (CH)
- ORCID
- Braun, Fabian
- Venue
- 2016 Computing in Cardiology Conference (CinC)
- Publisher
- Computing in Cardiology
- Published
- 2016-09-14
- Volume
- 43
- ISSN
- 2325-887X (ISSN-L)
- OpenAlex
- W2575479824
- Cited by
- 28
- References
- 5
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 3 · 2022: 3 · 2021: 4 · 2020: 6 · 2019: 4 · 2018: 3 · 2017: 2
- FWCI
- 6.01
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Computing in cardiology (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Keywords
- imaging photoplethysmography, heart rate estimation, face, region of interest selection, power spectral density, frons, blood volume changes, face segmentation, color maps
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