Lower limb biomechanics in individuals with chronic ankle instability during gait: a case‐control study
Bibliographic record
Abstract
BACKGROUND: Individuals with chronic ankle instability (CAI) exhibit many biomechanical changes to lower limbs during walking. However, only a few studies have investigated the differences in lower limb biomechanics of individuals with CAI compared to healthy controls using a comprehensive approach including kinematic, kinetic and electromyography (EMG) measures. Consequently, the theoretical framework explaining the biomechanical adaptations in individuals with CAI is mostly based on the results of studies including heterogenous methods and participants' specificities (e.g., level of disability). More studies using a comprehensive approach are needed to better understand the biomechanical adaptations associated with CAI. The objective of this case-control study was to identify the kinematic, kinetic and EMG differences between individuals with CAI and healthy controls during walking. METHODS: Twenty-eight individuals with CAI and 26 healthy controls were recruited to walk at a self-selected speed during which lower limb kinematics, kinetics and EMG were analysed. Ankle and knee angles and moments as well as gluteus medius, vastus lateralis, gastrocnemius lateralis, peroneus longus and tibialis anterior muscles activity were compared between the CAI and control groups using one-dimensional statistical parametric mapping. RESULTS: The CAI group exhibited greater ankle inversion angles from 14 to 48% of the stance phase (%SP) (p = 0.008), ankle eversion moments from 40 to 78%SP (p < 0.001), knee abduction moments from 3 to 6%SP and peroneus longus muscle activity from 0 to 15%SP (p = 0.003) and 60 to 76%SP (p = 0.003) compared to the control group. No significant between-group differences in ankle sagittal and transverse angles and moments, knee angles, knee sagittal and transverse moments as well as gluteus medius, vastus lateralis, gastrocnemius lateralis and tibialis anterior muscles activity were found. CONCLUSIONS: During the first half of the stance phase, individuals with CAI could be at more risk of sustaining recurrent LAS mostly due to greater ankle inversion angles. However, the greater ankle eversion moments and peroneus longus muscle activity during the second half of the stance phase were an efficient mechanism to correct this maladaptive gait pattern and allowed to attenuate the faulty ankle movements during the pre-swing phase.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".