The Efficacy of Combined Physical and Mental Practice in the Learning of a Foot-Sequence Task after Stroke: A Case Report
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of mental practice on the learning of a sequential task for the lower limb in a patient with a hemiparesis resulting from a stroke. DESIGN: A single-case study. SETTING: Research laboratory of a university-affiliated rehabilitation center. PATIENT: A right-handed 38-year-old man who had suffered a left hemorrhagic subcortical stroke 4 months prior. INTERVENTION: The patient practiced a serial response time task with the lower limb in 3 distinct training phases over a period of 5 weeks: 2 weeks of physical practice, 1 week of combined physical and mental practice, and then 2 weeks of mental practice alone. MAIN OUTCOME MEASURES: Performance on the task measured through errors and response times. Imagery abilities measured through questionnaires. RESULTS: The patient's average response time improved significantly during the 1st 5 days of physical practice (26%) but then failed to show further improvement during the following week of physical practice. The combination of mental and physical practice during the 3rd week yielded additional improvement (10.3%), whereas the following 2 weeks of mental practice resulted in a marginal increase in performance (2.2%). CONCLUSION: The findings show that mental practice, when combined with physical practice, can improve the performance of a sequential motor skill in people who had a stroke, and suggest that mental practice could play a role in the retention of newly acquired abilities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| 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".