The role of the ankle plantar flexor muscles in trip recovery during walking: a computational modeling study
Bibliographic record
Abstract
Background Reactive lower limb muscle function during walking plays a role in balance, stability, and ultimately fall prevention. The objective of this study was to evaluate muscle and joint function used to regain balance after trip-based perturbations during walking. Research question How are lower limb muscles used to recover from external tripping during walking? Method The dominant legs of 20 healthy adult participants with similar athletic backgrounds were tripped using a split-belt instrumented treadmill. High- and medium-intensity trips were simulated by deceleration of the dominant leg at initial contact from the speed of 1.1 m/s to 0 m/s and back to 1.1 m/s in 0.4 s and 0.8 s, respectively. Lower limb kinematics, kinetics, and muscle forces following perturbations were computed to pre-perturbation values using statistical parametric mapping (SPM) paired t-test. Results A greater ankle dorsiflexion angle (mean difference: 5.3°), ankle plantar flexion moment (mean difference: 0.6Nm/kg ), and gastrocnemius and soleus muscle forces (mean difference: 4.27N/kg and 13.56N/kg for GAS and SOL, respectively) were observed post-perturbation step despite the magnitude of the perturbation. Significance This study concludes that adequate timely response of ankle function during a compensatory step is required for a successful recovery after tripping during walking in young healthy adults. Weakness in plantar flexors suggests insufficient ankle moments, which ultimately can result in falls. The findings of this paper can be used as a reference for the joint moments and range of motion needed to recover trips in the design of assistive devices. In addition to that, clinicians can use the estimated values of muscle forces and the pattern of muscle activities to design targeted training in fall prevention among the elderly.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".