Evidence map›Paper›PMID 33923469›Full record

ReviewBiosensors2021

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring.

Jesse Fine, Kimberly L Branan, Andres J Rodriguez, Tananant Boonya-Ananta, Ajmal, Jessica C Ramella-Roman, Michael J McShane, Gerard L Coté

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
153citing papers in PubMed, 7 pooled it
17.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

153 citing papers in PubMed, 7 syntheses or guidelines pooled it, 299 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Guideline
  6. Pooled it
  7. Pooled it
  8. Review
  9. Disparities in Blood Pressure Measurement.Current hypertension reports · 2026
    Review
  10. Article
  11. Guidelines for rigor and reproducibility of heart rate variability within human cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2026
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Accuracy of VOMayo Clinic proceedings. Digital health · 2026
    Article
  18. Review
  19. Article
  20. Article

93 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Jesse FineDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Kimberly L BrananDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Andres J RodriguezDepartment of Biomedical Engineering, Florida International University, Miami, FL 33174, USA.
Tananant Boonya-AnantaDepartment of Biomedical Engineering, Florida International University, Miami, FL 33174, USA.
AjmalDepartment of Biomedical Engineering, Florida International University, Miami, FL 33174, USA.
Jessica C Ramella-RomanDepartment of Biomedical Engineering, Florida International University, Miami, FL 33174, USA.
Michael J McShaneDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Gerard L CotéDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-3164-9625
Florida International University · USTexas A&M University · US

Funding

National Science Foundation 1648451
6 · The paper itself

Abstract

Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

Indexed as

Monitoring, PhysiologicPhotoplethysmographyArtifactsBlood PressureHeart RateHumansRespirationSignal Processing, Computer-AssistedWearable Electronic Devicescardiovascular diseasephotoplethysmographyremote health

Identifiers

PMID33923469
PMCPMC8073123
OpenAlexW3155015885

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.