ReviewCommunications medicine2024
Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment.
Review in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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.
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Who cites it
14 citing papers in PubMed.
- Artificial Intelligence Enabled Diagnostics Using Photoplethysmography (PPG): Beyond SpOLife (Basel, Switzerland) · 2026Review
- Mechanical Contact Conditions in Wearable Reflectance Photoplethysmography: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Quantitative evaluation of skin pigmentation effects on photoplethysmography using vascular finger phantoms and Monte Carlo simulation.Journal of biomedical optics · 2026Article
- Arterial blood pressure waveform reconstruction estimation from PPG using TCN-BiLSTM.American heart journal plus : cardiology research and practice · 2026Article
- Wearables for Telemonitoring in ATTR-Amyloidosis: Current Perspectives.Sensors (Basel, Switzerland) · 2026Review
- Hypertension in Women Across the Life Cycle: Unique Aspects and Challenges.Current hypertension reports · 2026Review
- Deep learning-integrated multilayer thermal gradient sensing platform for real-time blood flow monitoring.Science advances · 2026Article
- Pulse Waveform Changes During Vasopressor Therapy Assessed Using Remote Photoplethysmography: A Case Series.Journal of clinical medicine · 2026Article
- The Challenge of Measuring Exercise: Advancing Metrological Barriers in Wearable Sensing.JMIR mHealth and uHealth · 2025Review
- The arterial stiffness and pulse pressure are predictors of intraocular pressure in a middle-aged population.Scientific reports · 2025Article
- Combating cardiovascular disease disparities: The potential role of artificial intelligence.American journal of preventive cardiology · 2025Article
- A feasibility study on non-invasive and non-contact jugular venous pulse measurement using 60 GHz FMCW radar.Royal Society open science · 2025Article
- A method for blood pressure hydrostatic pressure correction using wearable inertial sensors and deep learning.Npj biosensing · 2025Article
- Photoplethysmography Features Correlated with Blood Pressure Changes.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Photoplethysmography (PPG) is a non-invasive optical technique that measures changes in blood volume in the microvascular tissue bed of the body. While it shows potential as a clinical tool for blood pressure (BP) assessment and hypertension management, several sources of error can affect its performance. One such source is the PPG-based algorithm, which can lead to measurement bias and inaccuracy. Here, we review seven widely used measures to assess PPG-based algorithm performance and recommend implementing standardized error evaluation steps in their development. This standardization can reduce bias and improve the reliability and accuracy of PPG-based BP estimation, leading to better health outcomes for patients managing hypertension.
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Registered trials
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.