Large muscle group movements during sleep in healthy people: normative values and correlation to sleep features
Bibliographic record
Abstract
STUDY OBJECTIVES: To investigate the frequency and characteristics of large muscle group movements (LMMs) during sleep in healthy adults. METHODS: LMMs were scored following the International Restless Legs Syndrome Study Group criteria in 100 healthy participants aged 19-77 years. A LMM was defined as a temporally overlapping increase in EMG activity and/or the occurrence of movement artifacts in at least two channels. LMM indices and durations in total sleep time (TST), NREM and REM sleep, and association with arousals, awakenings, and/or respiratory events were calculated. Correlations of LMMs indices and durations with sleep architecture, respiratory and motor events, and subjective sleep quality were investigated. RESULTS: Median LMMs index in TST was 6.8/h (interquartile range (IQR), 4.5-10.8/h), median mean duration 12.4 s (IQR 10.7-14.4 s). Mean LMMs duration was longer in NREM (median 12.7 s, IQR 11.1-15.2 s) versus REM sleep (median 10.3 s, IQR 8.0-13.5s), p < 0.001. LMMs associated with awakening increased with age (p = 0.029). LMMs indices in TST were higher in men than women (p = 0.018). LMMs indices correlated positively with N1 sleep percentage (ρ = 0.49, p < 0.001), arousal index (ρ = 0.40, p = 0.002), sleep stages shift index (ρ = 0.43, p < 0.001, apnea index (ρ = 0.36, p = 0.017), and video-visible movements indices (ρ = 0.45, p < 0.001), and negatively with N3 sleep (ρ = -0.38, p= 0.004) percentage. CONCLUSIONS: This is the first study providing normative data on LMMs frequency in healthy adults. LMMs are a ubiquitous phenomenon often associated with other events. Correlation with arousals and respiratory events suggests a potential clinical significance of LMMs in adults that awaits further investigation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".