On-line mutability of step direction during rapid stepping reactions evoked by postural perturbation
Bibliographic record
Abstract
Stepping reactions are often triggered rapidly in response to loss of balance. It has been unclear whether spatial step parameters are defined at time of step-initiation or whether they can be modulated online, during step execution, in response to sensory feedback about the evolving state of instability. This study explored the capacity to actively alter step direction subsequent to step initiation in six healthy young-adult subjects. To elicit forward- step reactions, subjects were released suddenly from a tethered forward lean. A second perturbation (medio-lateral supportsurface translation) was applied at lags of 0–200 ms. Active reaction to the second perturbation was determined primarily through analysis of swing-leg hip-abductor activation. In addition, to gauge the biomechanical consequence of the changes in muscle activation, we compared the measured medio-lateral swing-foot displacement to that predicted by a simple passive mechanical model. Perturbations at 0–100 ms lag evoked active medio-lateral swing-foot deviation, allowing balance to be recovered with a single step. However, when the second perturbation occurred near foot-off (200-ms lag), there was no evidence of active alteration of step direction and subjects typically required additional steps to recover balance. The results suggest that step direction can be reparameterized during early stages of stepping reactions, but that step direction was not actively modulated in response to perturbation arising near start of 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 | 0.000 | 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) | 0.002 | 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".