Neuromechanical characterization of the abductor hallucis and its potential role in upright postural control
Bibliographic record
Abstract
There is growing evidence to support a role for the abductor hallucis (AH) in standing balance control; however, functional properties of the muscle that may provide more insight into AH's specific contribution to upright posture have yet to be characterized. This study was conducted to quantify functional neuromechanical properties of the AH and correlate the measures with standing balance variables. We quantified strength and voluntary activation during maximal voluntary isometric contractions of the great toe abductor in nine (3 females and 6 males) healthy, young participants. During electrically evoked twitch and tetanic contractions, we measured great toe abduction peak force and constructed a force-frequency curve. We also evaluated peak abduction force, contraction time (CT), half-relaxation time (HRT), rate of force development (RFD), and relaxation rate (RR) from twitch contractions evoked using doublet stimuli. Strength, VA, CT, HRT, RFD, and RR were correlated to centre of pressure standard deviation (COP SD) and velocity (COP VEL) variables of the traditional COP trace and its rambling and trembling components during single-legged stance. AH twitch properties (e.g., CT: 169.8 ± 32.3 ms; HRT: 124.1 ± 29.2 ms) and force-frequency curve were similar to other slow contractile muscles. Contractile speed related negatively with COP VEL, suggesting AH may be appropriate for slow, prolonged tasks such as ongoing postural balance control. Correlation coefficient outcomes for all variables were similar between rambling and trembling components. Our results provide further evidence for the importance of AH neuromechanical function for standing balance control, at least during a challenging single-legged posture.
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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) | 0.001 | 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".