SynthesisIEEE transactions on bio-medical engineering2024
Wearable Blood Pressure Monitoring Devices: Understanding Heterogeneity in Design and Evaluation.
Synthesis in IEEE transactions on bio-medical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Artificial Intelligence-Enhanced Wearable Blood Pressure Monitoring in Resource-Limited Settings: A Co-Design of Sensors, Model, and Deployment.Nano-micro letters · 2026Review
- Cuffless Noninvasive Continuous Blood Pressure Monitoring Using Superficial Temporal Arterial Tonometry.IEEE open journal of engineering in medicine and biology · 2026Article
- Robust Estimation of Unsteady Beat-to-Beat Systolic Blood Pressure Trends Using Photoplethysmography Contextual Cycles.Sensors (Basel, Switzerland) · 2025Article
- UTransBPNet for cuffless and calibration-free blood pressure estimation under dynamic conditions.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveRapid advances in cuffless blood pressure (BP) monitoring have the potential to radically transform clinical care for cardiovascular health. However, due to the large heterogeneity in device design and evaluation, it is difficult to critically and quantitatively evaluate research progress. In this two-part manuscript, we provide a principled way of describing and accounting for heterogeneity in device and study design.
methodsWe first provide an overview of foundational elements and design principles of three critical aspects: 1) sensors and systems, 2) pre-processing and feature extraction, and 3) BP estimation algorithms. Then, we critically analyze the state-of-the-art methods via a systematic review.
resultsFirst, we find large heterogeneity in study designs, making fair comparisons extremely challenging. Moreover, many study designs have data leakage and are underpowered. We suggest a first open-contribution BP estimation benchmark for standardization. Next, we observe that BP distribution in the study sample and the time between calibration and test in emerging personalized devices confound BP estimation error. We suggest accounting for these using a convenient metric coined "explained deviation". Finally, we complement this manuscript with a website, https://wearablebp.github.io, containing a bibliography, meta-analysis results, datasets, and benchmarks, providing a timely plaWorm to understand state-of-the-art devices.
conclusionThere is large heterogeneity in device and study design, which should be carefully accounted for when designing, comparing, and contrasting studies. SIGNIFICANCE: Our findings will allow readers to parse out the heterogeneous literature and move toward promising directions for safer and more reliable devices in clinical practice and beyond.
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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.