Novel Cuffless Blood Pressure Estimation Method Using a Bayesian Hierarchical Model
Bibliographic record
Abstract
Continuous blood pressure (BP) monitoring is important for the prevention and early diagnosis of cardiovascular diseases. Cuffless BP estimation using pulse arrival time (PAT) via a mathematical model which enables continuous BP measurement has recently become a popular research topic. In this study, simultaneous biomedical signals from ten healthy subjects were acquired by electrocardiogram (ECG) and photoplethysmogram (PPG) sensors and the continuous reference BP data were collected by a cuff-based Finometer PRO BP monitor. A hierarchical model was applied to estimate the parameters of a nonlinear model which in turn is used to estimate systolic blood pressure (SBP) using PAT with few calibration measurements. The mean absolute difference (MAD) between the estimated SBP and reference SBP is 4.35±1.43 mmHg using the proposed hierarchical model with three calibration measurements and is 4.36±1.17 mmHg with a single calibration measurement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".