Cited by 209Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlCardiovascular Health and Disease Prevention

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The Advantages of Wearable Green Reflected Photoplethysmography

Maeda, Yuka, Sekine, Masaki, Tamura, Toshiyo·2011·Journal of Medical Systems

DOI 10.1007/s10916-010-9506-z

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Abstract

This report evaluates the efficacy of reflected-type green light photoplethysmography (green light PPG). Transmitted infrared light was used for PPG and the arterial pulse was monitored transcutaneously. The reflected PPG signal contains AC components based on the heartbeat-related signal from the arterial blood flow and DC components, which include reflectance and scattering from tissue. Generally, changes in AC components are monitored, but the DC components play an important role during heat stress. In this study, we compared the signal of green light PPG to infrared PPG and ECG during heat stress. The wavelengths of the green and infrared light were 525 nm and 880 nm, respectively. Experiments were performed on young healthy subjects in cold (10°C), hot (45°C), and normal environments. The pulse rates were compared among three measurement devices and the AC and DC components of the PPG signal were evaluated during heat stress. The pulse rates obtained from green light PPG were strongly correlated with the R-R interval of an electrocardiogram in all environments, but those obtained from infrared light PPG displayed a weaker correlation with cold exposure. The AC components were of similar signal output for both wavelengths during heat stress. Also, the DC components for green light PPG were similar during heat stress, but showed less signal output for infrared light PPG during hot exposure. The main reason for the reduced DC components was speculated to be the increased blood flow at the vascular bed. Therefore, reflected green light PPG can be useful for pulse rate monitoring because it is less influenced by the tissue and vein region.

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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
The Optics of Human Skin
Anderson, R. R., & Parrish, J. A. (1981) · Journal of Investigative Dermatology · doi:10.1111/1523-1747.ep12479191 · Cited by 2,456
Mobile monitoring with wearable photoplethysmographic biosensors
Asada, H. H., Shaltis, P., Reisner, A., Rhee, S., & Hutchinson, R. C. (2003) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2003.1213624 · Cited by 466
THE BLOOD SUPPLY OF VARIOUS SKIN AREAS AS ESTIMATED BY THE PHOTOELECTRIC PLETHYSMOGRAPH
Hertzman, A. B. (1938) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1938.124.2.328 · Cited by 460
Pulsed multifrequency photoplethysmograph
Giltvedt, J., Sira, A., & Helme, P. (1984) · Medical & Biological Engineering & Computing · doi:10.1007/bf02442745 · Cited by 47
Green Light Photoplethysmography Monitoring of Free Flaps
Futran, N. D., Stack, B. C., Hollenbeak, C. S., & Scharf, J. (2000) · Archives of Otolaryngology - Head and Neck Surgery · doi:10.1001/archotol.126.5.659 · Cited by 35

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Authors: Maeda, Y., Sekine, M., & Tamura, T.
Affiliations: Chiba University (JP)
Corresponding author: Maeda, Yuka
ORCID: Maeda, Yuka
Tamura, Toshiyo
Venue: Journal of Medical Systems
Publisher: Springer Science and Business Media LLC
Published: 2010-05-18
Volume: 35
Issue: 5
Pages: 829-834
ISSN: 0148-5598 (ISSN-L)
1573-689X
DOI: 10.1007/s10916-010-9506-z
OpenAlex: W2040137929
Cited by: 209
References: 6
Citations by year: 2026: 12 · 2025: 23 · 2024: 15 · 2023: 20 · 2022: 22 · 2021: 25 · 2020: 15 · 2019: 17 · 2018: 13 · 2017: 19 · 2016: 5 · 2015: 9 · 2014: 7 · 2013: 3 · 2012: 1
FWCI: 1.32
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Medical Systems (publishedVersion)
PubMed (publishedVersion)
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 › Cardiovascular Health and Disease Prevention
Keywords: heat stress, pulse rate monitoring, wearable sensors, cold exposure, vascular blood flow
MeSH terms: Adult, Blood Pressure Determination, Color, Humans, Infrared Rays, Monitoring, Physiologic, Skin Temperature, Photoplethysmography, Young Adult, Wavelet Analysis

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