The effect of tendon vibration on motor unit activity, intermuscular coherence and force steadiness in the elbow flexors of males and females
Bibliographic record
Abstract
BACKGROUND: Compartmentalized responses in motor unit (MU) activity of the short head (SH) and long head (LH) of the biceps brachii are observed following forearm position change. Differential muscle spindle afferent distribution has been proposed as a potential mechanism underlying this behaviour. Tendon vibration is an effective, non-invasive method of increasing muscle spindle afferent activity of a target muscle group offering a paradigm in which this hypothesis may be investigated further. AIM: To determine the effect of tendon vibration on MU recruitment and discharge rates of the SH and LH, muscle activity of the elbow flexors and triceps brachii, intermuscular coherence among the SH, LH, brachioradialis and triceps brachii and force steadiness in young males and females during isometric elbow flexion. METHODS: Intramuscular electromyography (EMG) of the SH and LH, and surface EMG of the elbow flexors were recorded pre- and post-vibration during low-force isometric contractions. Motor unit recruitment thresholds, MU discharge rates and MU discharge variability; surface EMG amplitude, intermuscular coherence and force steadiness were determined pre- and post-vibration. RESULTS: Differential changes in all MU properties, EMG amplitude and intermuscular coherence were observed among elbow flexors. Although MU properties exhibited differential changes, they accounted for little variance in isometric force steadiness. However, intermuscular EMG coherence among all muscles investigated was reduced post-vibration. CONCLUSION: Uncoupling of common oscillatory input as a result of differential muscle spindle afferent inputs to elbow flexors may be responsible for the reduction in force steadiness following tendon vibration and a forearm position change.
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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 | 0.000 | 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) | 0.003 | 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".