ReviewAPL bioengineering2024
A review: Blood pressure monitoring based on PPG and circadian rhythm.
Review in APL bioengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- A wearable cuffless blood pressure monitoring system: real-time measurement using force sensing and waveform analysis.Journal of clinical monitoring and computing · 2026Article
- Mechanical Contact Conditions in Wearable Reflectance Photoplethysmography: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Consumer Smartwatch Technology in Health and Performance Research: Validity, Limitations, and Real-World Applications.Sensors (Basel, Switzerland) · 2026Review
- A wearable fiber-optoacoustic interface for continuous deep-tissue hemodynamics in MRI environments.Photoacoustics · 2026Article
- Comparison of heart rate measurement accuracy among commercially available photoplethysmography-based wearable devices across exercise intensities.Physical activity and nutrition · 2026Article
- A multitask Transformer-VAE framework for robust PPG denoising and atrial fibrillation screening.BMC medical imaging · 2026Article
- Intrinsic PPG-ECG Coupling for Accurate and Low-Power Blood Pressure Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Optical methods for cuffless blood pressure measurements.Biophotonics discovery · 2026Review
- Comparing the accuracy of continuous blood pressure monitoring using wearable cuffless devices with conventional 24-hour ambulatory blood pressure monitoring: A systematic review and meta-analysis.American journal of preventive cardiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The demand for ambulatory blood pressure monitoring (ABPM) is increasing due to the global rise in cardiovascular disease patients. However, conventional ABPM methods are discontinuous and can disrupt daily activities and sleep patterns. Photoplethysmography (PPG) is gaining attention from researchers due to its simplicity, portability, affordability, and ease of signal acquisition. This paper critically examines the advancements achieved in the technology of PPG-guided noninvasive blood pressure (BP) monitoring and explores future opportunities. We have performed a literature search using the Web of Science and PubMed search engines, from January 2018 to October 2023, for PPG signal quality assessment (SQA), cuffless BP estimation using single PPG, and associations between circadian rhythm and BP. Based on this foundation, we first examine the impact of PPG signal quality on blood pressure estimation results while focusing on methods for assessing PPG signal quality. Subsequently, the methods documented for estimating cuff-free BP from PPG signals are summarized. Furthermore, the study examines how individual differences affect the accuracy of BP estimation, incorporating the factors that influence arterial blood pressure (ABP) and elucidating the impact of circadian rhythm on blood pressure. Finally, there will be a summary of the study's findings and suggestions for future research directions.
Identifiers
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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.