Relationship of Cognitive Functions and Physical Activities in Persons with Chronic Stroke
Bibliographic record
Abstract
Purpose : The purpose of this study was to evaluate the relationship between physical performance, such as gait and postural control, and cognition on as assessed by clinical tools in individuals with chronic hemiparetic stroke.Methods : Twenty-six patients who had hemiparetic stroke participated in this study, and were evaluated four common clinical measurements, including the Berg balance scale (BBS), 10 meter walk test (10MWT), 6 minute walking test (6MWT), and Montreal cognitive assessment (MoCA). Multiple regression analysis was used BBS score, 10MWT, and 6MWT as the dependent variables; MoCA score, post-stroke duration, age, and affected side as independent variables.Results : In the regression equation of the BBS score, the correlation coefficient (r) was 0.875, the coefficient of determination (R2) was 0.786, and the MoCA score was the most important variable for determining the BBS score. In the regression equation for the 10MWT, ther was 0.888, the R2 was 0.999, and the MoCA score was the most important variable for determining 10MWT. Finally, the r was 0.777, the R2 was 0.998, and the MoCA score was the most important variable for determining 6MWT in the regression equation of the 6MWT.Conclusion : The results show that cognitive abilities affect gait proficiencies in individuals with chronic hemiparetic stroke. Therefore, these results suggest that cognitive tests are necessary for examining and evaluating the abilities of postural control and gait performance for chronic stroke patients in research and clinical environments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".