U-shaped Patterns in HRV From a Polysomnographic Point of View: a Quantitative Analysis
Bibliographic record
Abstract
U-shaped patterns are acceleration-deceleration periods in RR interval series.These relatively short time events (average duration 29.8±4.1 s) are the most laminar structures in the night-time recordings.The aim of this study is a analysis of sleep events occurring during U-shaped patterns in polysomnography (PSG) recordings obtained from Sleep Heart Health Study database.500 PSG recordings were analyzed.U-shaped patterns were detected and categorized based on sleep stages, body position, respiratory events and EEG arousals.4202 U-shaped patterns were found in 463 recordings.The majority of U-shaped patterns coincide with EEG arousals (73.9%).48% of the patterns occurred at sleep phase changes.Most of the U-shaped patterns were associated with the Wake phase (61%).U-shaped patterns occurred at the position changes in 22.6% of cases.Analysis of respiratory events showed that Ushaped patterns occurred during hypopnea in 32.3% of the cases, CSA -1.7%, OSA -0.8% and desaturation -18.6%.The quantitative analysis of PSG recordings is a first step to discover the origin of the phenomenon of Ushaped patterns.These first observations show that the Ushaped patterns are strongly associated with EEG arousals and may play role in sleep regulation.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".