Coefficient-free blood pressure estimation based on arterial lumen area oscillations in oscillometric methods
Bibliographic record
Abstract
In this paper we present a novel algorithm destined to estimate systolic and diastolic blood pressures from lumen area oscillations of vessel underneath the cuff by using automated oscillometric method. This algorithm is composed of three procedures which process only the diastolic region information of oscillometric waveform (OMW) from 80 mmHg to 20 mmHg, a domain which is considered a low cuff pressure region. The standard oscillometric methods need inflating the cuff to Supra Systolic Pressure (SSBP) and, as such, require a deflation time proportionally longer than our method. Because of the relative low inflation pressure, our method represents a viable option for patients who need to be monitored continuously, since, in such circumstances, the cuff is not allowed to be inflated to higher pressures for longer periods of time. We developed a unified algorithm composed of three integrated procedures which are all based on the arterial lumen area oscillation model at diastolic region to estimate blood pressure. The first procedure estimates the compliance c of the blood vessel. The second procedure uses c and estimates the maximum lumen area (Am), lumen area at mean arterial pressure - MAP (40) and the systolic arterial pressure (SBP) from the peaks of the OMW pulses. The third procedure uses c, Am, A0 found above to estimate diastolic arterial pressure (DBP) from the troughs of the OMW pulses. The OMW is obtained by filtering the cuff deflation curve (CDC) with a 2ndorder Butterworth band pass filter and which has cut-off frequencies of 0.5 to 20 Hz. The proposed method avoids using empirical systolic and diastolic ratios for estimation of blood pressure (like the popular maximum amplitude algorithm - MAA), but rather employs the least square method to optimize the lumen area oscillations model for targeted parameters. We applied this method on 150 oscillometric traces recorded from 10 healthy subjects composed of males and females from 25 to 63 years old, and validated the results with values measured by an Omron device that served as reference for each recording. Results are encouraging as mean absolute errors of estimated values from the Omron references over 150 recordings are 5.13 mmHg in terms of SBP and 3.18 mmHg for DBP with the standard deviation of errors of 3.60 mmHg and 2.58 mmHg respectively.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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".