Reduced Kinematic Redundancy and Motor Equivalence During Whole-Body Reaching in Individuals With Chronic Stroke
Bibliographic record
Abstract
Kinematic redundancy of the human body provides abundant movement patterns to accomplish the same motor goals (motor equivalence). Compensatory movement patterns such as excessive trunk displacement in stroke subjects during reaching can be viewed as a consequence of the motor equivalent process to accomplish a task despite limited available ranges in some joints. However, despite compensations, the ability to adapt reaching performance when perturbations occur may still be limited when condition-specific changes of joint angles are required. We addressed this hypothesis in individuals with and without stroke for reaching a target placed beyond arm reach in standing while flexing the hips (free-hip condition). In randomly selected trials, hip flexion was unexpectedly blocked, forcing subjects to take a step (blocked-hip condition). In additional trials, subjects took an intentional step while reaching the target (intentional-step condition). In blocked-hip trials, healthy subjects maintained smooth and precise endpoint trajectories by adapting temporal and spatial interjoint coordination to neutralize the effect of the perturbation. However, the ability to produce motor equivalent solutions was reduced in subjects with stroke, evidenced by substantial overshoot errors in endpoint position, reduced movement smoothness and less adaptive elbow-shoulder interjoint coordination. Movement adaptability was more limited in stroke subjects who used more compensatory movements for unperturbed reaching. Results suggest that subjects with mild-to-moderate stroke only partially adapted arm joint movements to maintain reaching performance. Therapeutic efforts to enhance the ability of individuals with stroke to find a larger number of task-relevant motor solutions (adaptability) may improve upper limb recovery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".