Abstract No: 368 Effects of Brain Gym Exercises on Cognitive Function in a Patient with Parkinson’s Disease: A Case Study
Bibliographic record
Abstract
Purpose: Non-motor symptoms, particularly cognitive decline, significantly impair the quality of life for Parkinson’s disease patients. Traditional treatments often fail to adequately address these symptoms. Considering this, the study is conducted with an intent to find if there is any effect of brain gym on cognition in a person with Parkinson’s disease. Relevance: Brain Gym is a kinesiological-based program designed to stimulate various brain regions, enhancing inter-hemispheric communication. The exercises engage multiple aspects of cognitive and physical function, offering an appealing alternative to conventional exercises for older adults. Participants: The study involved a 72-year-old female Parkinson’s patient (Modified Hoehn and Yahr Stage 2.5) with cognitive impairment and decreased quality of life. Methods: The patient participated in 12 sessions of 30-minute Brain Gym exercises over four weeks. Cognitive function and quality of life were assessed pre- and post-intervention using the Montreal Cognitive Assessment (MoCA) and Parkinson’s Impact Scale (PIMS), respectively. Analysis: The patient demonstrated improvement in MoCA score (from 17 to 27 out of 30) and PIMS score (from 20 to 15 out of 40) following the intervention. Results: Positive changes are seen in cognition by using Brain Gym exercises in a patient with Parkinson’s disease, hence improving the quality of life. Conclusion: This case study shows Brain Gym exercises can effectively improve cognition and quality of life in Parkinson’s disease management. Implications: While this single case study yielded positive results, further research with a larger patient group can be encouraged.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".