Reliable Respiratory Rate Estimation from a Bed Pressure Array
Why this work is in the frame
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Bibliographic record
Abstract
Unobtrusive sleep monitoring allows older adults to have continuous monitoring during the night in their own homes. We propose a method to reliably estimate respiratory rate using a bed-based pressure sensor array. Movements are detected prior to respiratory rate estimation and suppressed. The amount of movement during an estimate and a weighting for the estimate are used to create a reliability metric. The reliability metric is scored out of 100 for each sensor where high scores denote more reliable data. Once respiratory rates were calculated, the mean reliability metric determined the estimate reliability. Nocturnal data from a male and female participant was analyzed. Results show better accuracy and validity than both analysis without movement suppression and analysis with movement suppression but without postprocessing data fusion. While more than 50% of estimates include movement corruption, only 15% are unreliable and, moreover, removal of unreliable estimates significantly reduces estimate variance and provides validity estimation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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