The DOI matches its Crossref record; 277 of the 277 references it cites were found in a registry or an index.
Photoplethysmography and its application in clinical physiological measurement
Open accessAbstract
Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function.
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In the citing paper
“Prior research has suggested that PPG sensors used to measure the HR are liable to poor accuracy during activities with increased physical exertion or activities involving repetitive contractions of forearm skeletal muscles [36-38].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [37]
In the citing paper
“It has been suggested that during activities involving sustained muscle contractions or higher intensity exercises, the contact between the device’s PPG sensor and skin is decreased, leading to a disruption in the signal quality and causing poor quality data [36,37].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [37]
In the citing paper
“Firstly, surface EMG, increased electrode impedance, respiration induced baseline drift, and electrode contact movement can cause noise and motion artifacts.88”
From Wearable sensors for monitoring the physiological and biochemical profile of the athlete (2019) · cites this paper as [88]
In the citing paper
“However, the intrinsic PPG disturbances originating from physiological processes, such as respiration, vasoconstriction due to temperature changes or stress [57], have not been considered.”
From Modeling of artifacts in the wrist photoplethysmogram: Application to the detection of life-threatening arrhythmias (2021) · cites this paper as [57]
In the citing paper
“The photoplethysmogram (PPG) signal is a measure of arterial blood volume, which fluctuates with each heartbeat and is used by many wearables to monitor heart rate (HR).”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“The mechanisms underlying the PPG pulse wave shape are not yet fully understood [6].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“The shape is influenced not only by the incident wave transmitted through the arteries from the heart but also by reflected waves from a range of arterial sites [6].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“Cardiac output, monitored in peri-operative and critical care settings, has been estimated from pulse wave shape and low-frequency PPG variations”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“Thus, while the pulsating components of PPG are related to arterial blood volume, the non-pulsating component is a function of the average blood volume, respiration, the sympathetic nervous system, and thermoregulation [151].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [151]
In the citing paper
“These more recent wearable physical activity devices, which include a measure of heart rate, utilize photoplethysmography (PPG) to measure heart rate.”
From Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017) · cites this paper as [17]
In the citing paper
“PPG is a simple and low-cost optical technique that detects blood volume changes in the microvascular bed of tissue [17].”
From Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017) · cites this paper as [17]
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Metadata
- Authors
- Allen, J.
- Affiliations
- Freeman Hospital (GB)
- Corresponding author
- Allen, John
- ORCID
- Allen, John
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2007-02-20
- Volume
- 28
- Issue
- 3
- Pages
- R1-R39
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2083872334
- Cited by
- 3,967
- References
- 275
- Citations by year
- 2026: 308 · 2025: 292 · 2024: 310 · 2023: 317 · 2022: 323 · 2021: 314 · 2020: 291 · 2019: 304 · 2018: 299 · 2017: 227 · 2016: 185 · 2015: 216 · 2014: 159 · 2013: 132 · 2012: 86
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Physiological Measurement (publishedVersion)
- PubMed (publishedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
- Keywords
- photoplethysmography, blood volume changes, pulse wave analysis, non-invasive physiological monitoring, oxygen saturation, blood pressure measurement, cardiac output, autonomic function, peripheral vascular disease, vascular assessment, light-tissue interaction
- MeSH terms
- Autonomic Nervous System, Blood Vessels, Humans, Monitoring, Physiologic, Vascular Diseases, Photoplethysmography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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