Exergame-Based Program and Conventional Physiotherapy Based on Core Areas of the European Guideline Similarly Improve Gait and Cognition in People with Parkinson’s Disease: Randomized Clinical Trial
Bibliographic record
Abstract
Background:Gait impairments are among the most common and disabling symptoms of Parkinson’s disease and are especially aggravated in dual-task conditions. Interventions with conventional physical therapy improve gait cadence and speed, cognition, fear of falling, and freezing of gait. However, exergames have attracted interest in the treatment of people with Parkinson’s disease due to the characteristics of the training that benefit neuroplasticity and motor learning. Objective:The aim of this study was to analyze the effects of training based on Kinect exergames compared to conventional physiotherapeutic training based on core areas of the European physiotherapy guideline on functional mobility, gait, and cognitive functions. Materials and Methods:Thirty-eight people with idiopathic Parkinson’s disease were randomized into two groups and underwent 14 intervention sessions, twice a week, for 60 minutes each. The primary outcome was postural stability in gait, which was evaluated using the Functional Gait Assessment. Secondary outcomes were functional mobility and impact of the dual task assessed using the Timed & Up and Go Test; gait speed by the 10-meter Walk Test in single and dual task; and cognitive functions assessed through the Montreal Cognitive Assessment. Results:After training, there was an improvement in the Functional Gait Assessment and Timed & Up and Go Test. Conclusion:Interventions based on Kinect AdventuresTM games and conventional physiotherapy based on the central areas of the European guideline promoted similar improvements in gait stability and functional mobility of people with Parkinson’s disease, without differences between them. However, the benefits did not extend to cognitive function and other gait parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".