Estimation of Respiratory Rate and Heart Rate During Treadmill Tests Using Acoustic Sensor
Bibliographic record
Abstract
The objective was to test the robustness of an acoustic method to estimate respiratory rates (RR) during treadmill test. The accuracy was assessed by the comparison with simultaneous estimates from a capnograph, using as a common reference a pneumotachometer. Eight subjects without any pulmonary disease were enrolled. Tracheal sounds were acquired using a contact piezoelectric sensor placed on the subject's throat and analyzed using a combined investigation of the sound envelope and frequency content. The capnograph and pneumotachometer were coupled to a face mask worn by the subjects. There was a strong linear correlation between all three methods (r2ranged from 0.8 to 0.87), and the SEE ranged from 1.97 to 2.36. As a conclusion, the accuracy of the respiratory rate estimated from tracheal sounds on adult subjects during treadmill stress test was comparable to the accuracy of a commercial capnograph. The heart rate (HR) estimates can also be derived from carotid pulse using the same single sensor placed on the subject's throat. Compared to the pulse oximeter the results show an agreement of acoustic method with r2= 0.76 and SEE = 3.51
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".