Impaired corrective responses to postural perturbations of the arm in individuals with subacute stroke
Bibliographic record
Abstract
BACKGROUND: Stroke is known to alter muscle stretch responses following a perturbation, but little is known about the behavioural consequences of these altered feedback responses. Characterizing impairments in people with stroke in their interactions with the external environment may lead to better long term outcomes. This information can inform therapists about rehabilitation targets and help subjects with stroke avoid injury when moving in the world. METHODS: In this study, we developed a postural perturbation task to quantity upper limb function of subjects with subacute stroke (n = 38) and non-disabled controls (n = 74) to make rapid corrective responses with the arm. Subjects were instructed to maintain their hand at a target before and after a mechanical load was applied to the limb. Visual feedback of the hand was removed for half of the trials at perturbation onset. A number of parameters quantified subject performance, and impairment in performance was defined as outside the 95th percentile performance of control subjects. RESULTS: Individual subjects with stroke showed increased postural instability (44%), delayed motor responses (79%), delayed returns towards the spatial target (79%), and greater endpoint errors (74%). Several subjects also showed impairments in the temporal coordination of the elbow and shoulder joints when responding to the perturbation (47%). Interestingly, impairments in task parameters were often found for both arms of individual subjects with stroke (up to 58% for return time). Visual feedback did not improve performance on task parameters except for decreasing endpoint error for all subjects. Significant correlations between task performance and clinical measures were dependent on the arm assessed. CONCLUSIONS: This study used a simple postural perturbation task to highlight that subjects with stroke commonly have difficulties responding to mechanical disturbances that may have important implications for their ability to perform daily activities.
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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) | 0.001 | 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) | 0.002 | 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".