Examining the biomechanical mechanisms of restabilisation-phase stability control of compensatory stepping with increasing perturbation magnitudes and with failed balance recovery responses
Bibliographic record
Abstract
PROBLEM: Falls are an ever growing problem in Canada that can lead to physical injury. Falls occur when the Center of Mass (CoM) moves outside the borders of the Base of Support (BoS), putting the body in an unbalanced state. Following a balance perturbation, a compensatory step acts reactively to prevent falls via a forward step that increases the BoS. After foot-contact, the restabilisation phase creates stabilizing moments that act to slow and maintain the CoM within the BoS. However, no studies have looked at the how the restabilisation phase changes with increasing perturbation magnitudes, and when a compensatory step is unable to recover balance. PURPOSE: To assess the biomechanics of the compensatory stepping response and its restabilisation phase with increasing perturbation magnitudes, as well as when the compensatory step is unable to recover balance with a single step. METHOD: A maximum lean-and-release protocol was used to compare (1) participants successful balance responses at their initial and maximal lean angles and (2) successful and failed balance response tasks that occur at the same lean angle. RESULTS: Successful balance responses following larger perturbation magnitudes had a reduced step time, longer step length, and larger stabilizing moments during the restabilisation phase, but had a larger destabilizing moment at foot-contact and greater instability throughout the restabilisation phase, as well as a longer time to restabilisation. The failed balance response tasks relative to the successful responses had shorter step lengths, larger destabilizing moments and greater instability at foot-contact, and were unable to achieve restabilisation. CONCLUSION: The key to performing a successful balance recovery response appears to be producing a large and fast step that reduces the CoM velocity at foot-contact, increases stability at foot-contact, and allows for generating larger stabilizing moments in the restabilisation 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) | 0.000 | 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".