Characterization of Muscular Rest Periods (gaps) in Long-term EMG of Older Men and Women
Bibliographic record
Abstract
The ability to maintain functional independence in older adults is largely associated with the generation and control of purposeful movement. Laboratory studies indicate that with increasing age there is a decline in muscle strength and a decrease in force control. Limited studies are available on neuromuscular activity outside the laboratory in older adults, but initial data indicate that burst activity is greater in older adults compared with young adults and in women compared with men (Appl Physiol Nut Met 31 (S22), 2006). This difference in burst activity might be due to periods of silence in electromyography (EMG) activity. PURPOSE: To characterize periods of muscle silence (gaps) in young and old men and women for an 8-hour typical weekday. METHODS: EMG was recorded in the biceps brachii, triceps brachii, quadriceps femoris and hamstrings in 16 young (23 + 2.5 yrs; 8 men, 8 women) and 15 older (77 + 3.5 yrs; 8 men, 7 women) adults. A portable EMG device was utilized. Signals were pre-amplified (1000x), band pass filtered (20–450Hz), stored on a 512 MB flashcard and subsequently downloaded to Spike 2 for custom analysis. A gap was denned as an EMG interval <1% of the maximum isometric effort (MVE), and a duration of >0.1s. Total number of gaps, gap duration (sec), gap amplitude (% MVE), mean gap activity (% MVE) and gap rate (gaps/s) were assessed. RESULTS: The number of gaps recorded did not differ as a function of age (10%δ) or gender (14%δ). However, the mean duration (sec) of the gaps were ∼2 times longer in the young compared with old, and during periods of silence the amplitude and area of the gaps were also less (3-10%δ) in the young compared with the old. Gender differences were evident as mean duration of the gaps (sec) and area of the gaps (MVC*s) were longer (∼1.5 times) in men compared with women, yet gap amplitude (%MVC) was greater in women (∼0.8 times) compared with men. CONCLUSIONS: Shorter durations and higher amplitudes of gap activity during periods of EMG silence suggest that muscles of older adults are not as quiescent as muscles of young adults during periods of “rest”. As well, total gaps do not differ between genders but the duration and amplitudes which characterize a gap differ between men and women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".