Reduced gait stability in high-functioning poststroke individuals
Bibliographic record
Abstract
Falls during walking are a major cause of poststroke injury, and walking faster may decrease the ability to recover following a gait perturbation. We compared gait stability between high-functioning poststroke individuals and controls and evaluated the effect of gait speed on gait stability. Ten stroke subjects and ten age-matched controls walked on a self-paced treadmill at two speeds (matched/faster). Movement of the nonparetic/dominant leg was arrested unexpectedly at early swing. Poststroke individuals lowered the perturbed leg following perturbation (58% of cases) while controls maintained the leg elevated (49% of cases; P < 0.01). In poststroke individuals, double-support duration was restored later than in controls (4.6 ± 0.8 vs. 3.2 ± 0.3 strides; P < 0.007), and long-term phase shifts of arm and leg movements were larger and less coordinated on the paretic side. A moderate speed increase (~20%) enhanced the incidence of leg lowering in controls but not in stroke subjects. Faster walkers in both groups had a more coordinated response, limited to the nonparetic side in the stroke group. However, faster walkers were not more stable following perturbation. Our results suggest that gait perturbations can target basic control processes and identify neurological locomotor deficits in individuals with fall risk. Central regulation of body translation in space is involved in recovery of steady-state walking. Impaired descending control (stroke) decreases the ability of the motor system to recover from perturbations and regulate interlimb phase relationships, especially when changing gait speed. However, interlimb coordination may not be a major factor in the recovery of gait stability.
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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 | 0.001 | 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) | 0.001 | 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".