Feasibility and Efficacy of the Nintendo Wii Gaming System to Improve Balance Performance Post-Stroke: Protocol of a Phase II Randomized Controlled Trial in an Inpatient Rehabilitation Setting
Bibliographic record
Abstract
OBJECTIVE: Balance deficits following stroke are common and debilitating. Commercially available gaming systems, such as the Nintendo(®) (Kyoto, Japan) Wii™, have been widely adopted clinically; however, there is limited evidence supporting their feasibility and efficacy for improving balance performance following stroke. The aim of this trial is to investigate the clinical feasibility and efficacy of using the Nintendo Wii gaming system as an adjunct to standard care to improve balance performance following stroke in an inpatient rehabilitation setting. SUBJECTS AND METHODS: Thirty participants undergoing inpatient stroke rehabilitation will be recruited into this Phase II, single-blind, randomized controlled trial. Participants will be allocated into a Balance or Upper Limb Group, and both groups will perform activities using the Nintendo Wii in addition to their standard care. Participants will attend three 45-minute sessions per week, for a minimum of 2 and a maximum of 4 weeks. RESULTS: The main focus of the study is to investigate the feasibility of the intervention protocol. This will be evaluated through recruitment, retention, adherence, acceptability, and safety. The Step Test and Functional Reach Test will be the primary efficacy outcomes. Secondary outcomes will include force platform, mobility, and upper limb measures. Assessments will occur at baseline, 2 weeks, and 4 weeks after study entry. DISCUSSION: To the authors' knowledge, this will be the largest randomized clinical trial to investigate the feasibility and efficacy of the Nintendo Wii gaming system for improving balance performance in a stroke population. The results will inform the design of a Phase III multicenter trial.
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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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".