Free-living muscle activity in type 2 diabetes across whole-of-day, sitting, standing, and walking
Bibliographic record
Abstract
In adults with type 2 diabetes, we used thigh-worn accelerometers and electromyographic (EMG) shorts to investigate muscle activity in a free-living environment. Quadriceps, hamstring, and gluteal muscle EMG was normalized individually to that during isometric maximal voluntary contraction (%EMGMVC). Devices were worn concurrently by 18 participants (11 female) for an average of 3.2 days. Median EMG amplitude (aEMG) was assessed from all three muscle groups during the whole day and within accelerometer-derived sitting, standing, and walking time. Associations of muscle activity with the duration of these behaviours were explored via multiple linear regression adjusting for sex, age, body composition, and diabetes duration. Free-living aEMG for the whole day was 3.3%EMGMVC (range 1.6%–6.2%), for sitting 2.5%EMGMVC (1.8%–3.7%), for standing 6.3%EMGMVC (3.8%–19.8%), and for walking 19.8%EMGMVC (7.5%–34.1%). The aEMG varied between muscle groups, being generally higher in gluteal and hamstrings than quadriceps. Both sitting, standing, and walking aEMG in the hamstrings was positively associated with whole day aEMG. Furthermore, sitting aEMG in the hamstrings was inversely associated with sitting duration, and standing aEMG in the hamstrings with walking duration. People with type 2 diabetes have low overall muscle activity during daily living. Walking time may be an effective countermeasure against low daily muscle activity. High individual variability highlights potential to personalize recommendations on sitting, standing, and walking. Notably, the ability to activate hamstrings during these activities may support shorter sitting and longer walking durations in daily life.
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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 | 0.001 |
| 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".