Task-Oriented Intervention in Chronic Stroke
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to evaluate whether, after a task-oriented exercise program, the changes in clinical measures of balance and mobility were paralleled by changes in biomechanical parameters in subjects with chronic stroke. DESIGN: Ten stroke subjects took part in an 8-wk exercise program aimed at improving balance and mobility through various functional tasks. Subjects were evaluated before and after the exercise intervention. Clinical measures included the Berg Balance Scale and the Timed-Up-and-Go and laboratory measures included ground reaction forces and center of pressure displacement during four functional tasks. RESULTS: Stroke subjects showed significant improvements (P < 0.05) in the clinical measures after completing the exercise program. Significant improvements (P < 0.05) were also found in postural steadiness during tandem stance and stool touch and in force production through the paretic lower limb during sit-to-stand. This last result was strongly correlated (r = -0.93) with the improvements on the Timed-Up-and-Go after exercise intervention. In contrast, the increase in postural steadiness was poorly correlated with the improvements on the Berg Balance Scale. CONCLUSIONS: A task-oriented exercise program might improve both clinical and laboratory measures of balance and mobility in stroke subjects. However, several correlations between the changes in clinical and laboratory measures after exercise intervention were generally weak, indicating that these outcome measures assessed different components of improvements.
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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".