The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Influence of skin type and wavelength on light wave reflectance
Abstract
Purpose A new application of photoplethysmography (PPG) has emerged recently to provide the possibility of heart rate monitoring without a telemetric chest strap. The aim of this study was to determine if a new device could detect pulsation over a broad range of skin types, and what light wavelength would be most suitable for detecting the signals. A light emitting diode-based PPG system was used to detect changes in pulsatile blood flow on 23 apparently healthy individuals (11 male and 12 female, 20-59 years old) of varying skin types classified according to a questionnaire in combination with digital photographs with a skin type chart. Four different light wavelengths (470, 520, 630, and 880 nm) were tested. Normalized modulation level is calculated as the AC/DC component ratio and represents the change in flow over the underlying constant state of flow or perfusion.Results In the resting condition, green light wavelength (520 nm) displayed greater modulation (p < 0.001) than all the other wavelengths analyzed regardless of skin types. Type V (dark brown) skin type was significantly lower in modulation than all other skin types. In the exercise condition, both blue (470 nm) and green (520 nm) light wavelengths displayed greater signal-to-noise ratios than red (630 nm) or infrared (880 nm) light wavelengths (p < 0.001).Conclusions We concluded that a PPG-based device can detect pulsation across all skin types and that a greater resolution was obtained using a green light wavelength at rest and a green or blue light wavelength during exercise.
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In the citing paper
“increased melanin reduces signal penetration into the blood-containing dermis, attenuating the AC component of the PPG signal.”
From PPG-Based Heart Rate Accuracy in Hispanic Adults with Fitzpatrick III–V Skin Tones: An Evaluation of Body Composition and Skin-Tone Effects (2026) · cites this paper as [11]
In the citing paper
“consistent with optical absorption by melanin in the green band and reduced pulsatile content reaching the photodiode [10,11,28].”
From PPG-Based Heart Rate Accuracy in Hispanic Adults with Fitzpatrick III–V Skin Tones: An Evaluation of Body Composition and Skin-Tone Effects (2026) · cites this paper as [11]
In the citing paper
“previous research demonstrated that inaccurate PPG HR measurements occur up to 15% more frequently in dark skin as compared to light skin”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [25]
In the citing paper
“likely because darker skin contains more melanin which absorbs more green light than lighter skin.”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [25]
In the citing paper
“since optical HR measurements primarily measure green light absorption.24,25”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [25]
In the citing paper
“Effect size for the power analysis was based on a pilot study examining differences in light absorption across skin tones25 and was determined to be 0.3.”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [25]
In the citing paper
“there are only a small handful of studies that examine skin tone and accuracy rates directly1–3,11”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [3]
In the citing paper
“This finding is in contrast to previously reported studies finding wearables using green light technology had larger errors rates in tracking heart rate and energy expenditure for individuals with darker skin tones2, especially if exercising3.”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [3]
In the citing paper
“due to technological limitations of Photoplethysmography (PPG) green light signaling, these health constructs may not be as accurate for a population of people with darker skin tones2,3”
From Response To: Investigating sources of inaccuracy in wearable optical heart rate sensors (2021) · cites this paper as [3]
In the citing paper
“This effect has been documented by other investigators68 and it may account for some of the errors experienced by dark skin individuals utilizing wearable based on PPG68–71.”
From Synthetic photoplethysmography (PPG) of the radial artery through parallelized Monte Carlo and its correlation to body mass index (BMI) (2021) · cites this paper as [68]
In the citing paper
“Indeed, Fallow et al. found a better resolution using a green-light wavelength at rest and a green or blue-light wavelength in motion across all skin types [80].”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [80]
In the citing paper
“Studies on healthy adults with different skin pigmentation showed that red and green wavelengths could estimate oxygen saturation with good agreement and lower error ratio compared to the traditional pulse oximeter [30,80,102].”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [80]
In the citing paper
“Melanin attenuates the wavelength of the incident light and limits the penetration to the subcutaneous tissue because is high light-absorbing [80,101].”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [80]
In the citing paper
“Fallow et al. classified 23 healthy subjects (11 males and 12 females, 20–59 years old) finding that phototype-V (dark brown) skin type has a significant signal-to-noise ratio than all other skin types [80].”
From Skin pigmentation influence on pulse oximetry accuracy: a systematic review and bibliometric analysis (2022) · cites this paper as [80]
In the citing paper
“Fallow et al. identified that green wavelengths (520 nm) displayed greater accuracy in heart rate measurement regardless of skin type when compared to other wavelengths, both at rest and during exercise [20].”
From Accuracy of heart rate measurement with wrist-worn wearable devices in various skin tones: a systematic review (2023) · cites this paper as [20]
In the citing paper
“Studies have shown that green light lacks precision and accuracy, and may not read at all, when measuring heart rate in darker skin types [2].”
From Limiting racial disparities and bias for wearable devices in health science research (2020) · cites this paper as [2]
In the citing paper
“We note with deep concern that there is increasing evidence that these devices are not as accurate, and may not work at all, in people with darker skin tones [1, 2].”
From Limiting racial disparities and bias for wearable devices in health science research (2020) · cites this paper as [2]
In the citing paper
“Mean modulation, often termed the perfusion index, defined as the ratio of AC/DC, was significantly lower in Fitzpatrick V individuals than others for all wavelengths (p < 0.001).”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [52]
In the citing paper
“In the resting condition, green light had larger mean modulation (p < 0.001) than other wavelengths, and after exercise, blue and green had greater SNR ratios than red or infrared (p < 0.001).”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [52]
Citations
Cites
(2014) · Medical Entomology and Zoology · Cited by 9,400
Photoplethysmography and its application in clinical physiological measurement
Allen, J. (2007) · Physiological Measurement · doi:10.1088/0967-3334/28/3/r01 · Cited by 3,967
Age-predicted maximal heart rate revisited
Tanaka, H., Monahan, K. D., & Seals, D. R. (2001) · Journal of the American College of Cardiology · doi:10.1016/s0735-1097(00)01054-8 · Cited by 3,775 · cited 1×
“Indeed heart rate has been a useful and widely used index of physical exertion and intensities of effort during physical activity [10].”
BackgroundSelf-citationAnderson, R. R., & Parrish, J. A. (1981) · Journal of Investigative Dermatology · doi:10.1111/1523-1747.ep12479191 · Cited by 2,456
Physical Activity, Fitness, and Health
(2012) · Human Kinetics eBooks · doi:10.5040/9781718209107.part-001 · Cited by 739
Physical Activity, Fitness, and Health
Bouchard, C., Shephard, R. J., & Brubaker, P. H. (1994) · Medicine & Science in Sports & Exercise · doi:10.1249/00005768-199401000-00024 · Cited by 703
Zonios, G., Bykowski, J., & Kollias, N. (2001) · Journal of Investigative Dermatology · doi:10.1046/j.0022-202x.2001.01577.x · Cited by 477
Skin photoplethysmography — a review
Kamal, A. A. R., Harness, J. B., Irving, G., & Mearns, A. J. (1989) · Computer Methods and Programs in Biomedicine · doi:10.1016/0169-2607(89)90159-4 · Cited by 328 · cited 6×
“Normalized modulation level is calculated as the AC/DC component and represents the change in flow over the underlying constant state of flow or perfusion [1, 8].”
BackgroundMethodInfluentialExercise Prescription for the Elderly
Mazzeo, R. S., & Tanaka, H. (2001) · Sports Medicine · doi:10.2165/00007256-200131110-00003 · Cited by 303
Self-citationIshikawa-Takata, K. (2003) · American Journal of Hypertension · doi:10.1016/s0895-7061(03)00895-1 · Cited by 190
In vivo reflectance of blood and tissue as a function of light wavelength
Cui, W., Ostrander, L. E., & Lee, B. Y. (1990) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.55667 · Cited by 149
Reflection photoplethysmography of arterial-blood-volume pulses
Weinman, J., Hayat, A., & Raviv, G. (1977) · Medical & Biological Engineering & Computing · doi:10.1007/bf02441571 · Cited by 57
Dose–response issues from a biological perspective.
Haskell, W. L. (1994) · Cited by 45
Post‐exercise palpation of pulse rates: its applicability to habitual exercisers
DeVan, A. E., Lacy, B. K., Cortez‐Cooper, M. Y., & Tanaka, H. (2005) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/j.1600-0838.2004.409.x · Cited by 11
Self-citation
Cited by
Sorted by citations
Investigating sources of inaccuracy in wearable optical heart rate sensors
Bent, B., Goldstein, B. A., Kibbe, W. A., & Dunn, J. P. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0226-6 · Cited by 673
“Difference in green light mean absorption for different skin tones during activity was used to calculate effect size since optical HR measurements primarily measure green light absorption.(24,25) Based on the ANOVA power calculation, we required eight participants per skin tone category (6 skin tone categories on FP s…”
MethodPhotoplethysmogram Analysis and Applications: An Integrative Review
Park, J., Seok, H. S., Kim, S.-S., & Shin, H. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2021.808451 · Cited by 514
Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks
Reiss, A., Indlekofer, I., Schmidt, P., & Laerhoven, K. V. (2019) · Sensors · doi:10.3390/s19143079 · Cited by 383
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
“Further research should be conducted that analyzes the fidelity of the PPG waveform under these conditions, which would allow interpretation of which wavelengths can be used to derive more complicated parameters from PPG [52].”
MethodAccuracy of Heart Rate Watches: Implications for Weight Management
Wallen, M. P., Gomersall, S. R., Keating, S. E., Wisløff, U., & Coombes, J. S. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154420 · Cited by 336
Metadata
- Authors
- Fallow, B. A., Tarumi, T., & Tanaka, H.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Tanaka, Hirofumi
- Venue
- Journal of Clinical Monitoring and Computing
- Published
- 2013-02-09
- Volume
- 27
- Issue
- 3
- Pages
- 313-317
- ISSN
- 1387-1307 (ISSN-L)
- 1573-2614
- OpenAlex
- W2066932506
- Cited by
- 162
- References
- 14
- Citations by year
- 2026: 12 · 2025: 13 · 2024: 23 · 2023: 22 · 2022: 19 · 2021: 27 · 2020: 12 · 2019: 11 · 2018: 8 · 2017: 8 · 2016: 3 · 2015: 4
- FWCI
- 1.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Clinical Monitoring and Computing (publishedVersion)
- PubMed (publishedVersion)
- Texas ScholarWorks (Texas Digital Library) (submittedVersion)
- Funders
- Omron Healthcare
- 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 › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Keywords
- photoplethysmography, skin type, light wavelength, heart rate monitoring, pulsatile blood flow, signal-to-noise ratio, physical activity, green light, blue light, infrared radiation, skin pigmentation
- MeSH terms
- Adult, Female, Heart Rate, Humans, Light, Male, Middle Aged, Monitoring, Physiologic, Skin, Skin Pigmentation, Exercise, Photoplethysmography, Optical Phenomena, Young Adult, Signal-To-Noise Ratio
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