Wearable PPG Based BP Estimation Methods: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This meta-analysis and systematic review, conducted in accordance with PRISMA guidelines, explores the efficacy of cuff-less blood pressure (BP) monitoring methods, particularly focusing on photoplethysmogram-based technologies. This comprehensive analysis carefully searched prominent databases such as MEDLINE, PubMed, AMED, Embase, and IEEE-Xplore, encompassing 25 studies with a collective participant pool of 21 142 individuals. The study primarily investigates the accuracy and practicality of continuous BP estimation devices and algorithms, aiming to assess their suitability for daily or long-term, as well as their applicability and usability across a broad population. The mean disparities were 4.14 mmHg for systolic blood pressure (SBP) and 2.79 mmHg for diastolic blood pressure (DBP), highlighting a close congruence with established measurement techniques. An in-depth analysis into specific methodologies reveals that Pulse Waveform Analysis (PWA) demonstrates a more favorable performance compared to Pulse Wave Velocity (PWV) for both SBP and DBP, although these differences are not statistically significant. The findings indicate a promising future for wearable devices in short-term BP monitoring scenarios. Both PWA and PWV methods in wearable formats have shown considerable potential as effective tools for BP assessment. However, the study underscores the need for further research, particularly targeting hypertensive populations, to validate the long-term effectiveness and reliability of these wearables. Finally, this investigation is crucial for establishing the role of wearables in ongoing, reliable BP monitoring, especially when considered in conjunction with other health monitoring technologies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it