Use of the extended feasible stability region for assessing stability of perturbed walking
Bibliographic record
Abstract
Walking stability has been assessed through gait variability or existing biomechanical measures. However, such measures are unable to quantify the instantaneous risk of loss-of-balance as a function of gait parameters, body sway, and physiological and perturbation conditions. This study aimed to introduce and evaluate novel biomechanical measures for loss-of-balance under various perturbed walking conditions. We introduced the concept of 'Extended Feasible Stability Region (ExFSR)' that characterizes walking stability for the duration of an entire step. We proposed novel stability measures based on the proximity of the body's centre of mass (COM) position and velocity to the ExFSR limits. We quantified perturbed walking of fifteen non-disabled individuals and three individuals with a disability, and calculated our proposed ExFSR-based measures. 17.2% (32.5%) and 26.3% (34.0%) of the measured trajectories of the COM position and velocity during low (high) perturbations went outside the ExFSR limits, for non-disabled and disabled individuals, respectively. Besides, our proposed measures significantly correlated with measures previously suggested in the literature to assess gait stability, indicating a similar trend in gait stability revealed by them. The ExFSR-based measures facilitate our understanding on the biomechanical mechanisms of loss-of-balance and can contribute to the development of strategies for balance assessment.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".