Snoring sounds variability as a signature of obstructive sleep apnea
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
Snoring sounds vary significantly within and between snorers. In this study, the variation of snoring sounds and its association with obstructive sleep apnea (OSA) are quantified. Snoring sounds of 42 snorers with different degrees of obstructive sleep apnea and 15 non-OSA snorers were analyzed. The sounds were recorded by a microphone placed over the suprasternal notch of trachea, simultaneously with polysomnography (PSG) data over the entire night. We hypothesize that snoring sounds vary significantly within a subject depending on the level of obstruction, and thus the level of airflow. We also hypothesize that this variability is associated with the severity of OSA. For each individual, we extracted snoring sound segments from the respiratory recordings, and divided them into three classes: non-apneic, hypopneic, and post-apneic using their PSG information. Several features were extracted from the snoring sound segments, and compared using a nonparametric statistical test. The results show significant shift in the median of features among the snoring sound classes (p<0.00001) of an individual. In contrast to hypopneic and post-apneic classes, the characteristics of snoring sounds did not vary significantly over time in non-apneic class. Therefore, we used the total variation norm of each subject to classify the participants as OSA and non-OSA snorers. The results showed 92.9% sensitivity, 100% specificity and 96.4% accuracy.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 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