Non-invasive blood pressure measurement algorithm using neural networks
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
The oscillometric method is the most commonly used automatic monitoring blood pressure measurement method nowadays.Height-based and Slope-based criteria are the two general means used to determine the systolic and diastolic pressures; howeverthey are disputed for their accuracy. Thus, the auscultatory method continues to be the gold-standard for these measurements.In this paper a newly developed cuff with piezofilm sensors and a pressure sensor to collect signals from the brachial artery isinvestigated. Using Neural Networks to classify the acquired pressure signals in various regions, an algorithm is developed andimplemented in signal processing and heart beat/heart rate detection software. The algorithm is tested on 258 measurementsfrom 86 subjects and shows good conformance to the standards set out by the Association for the Advancement of Medical Instrumentation and British Hypertension Society grade A criteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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