Effects of Balance-Based Exergame Training With Variable Difficulty on Balance and Spatiotemporal Gait Outcomes in Adults With Mild Cognitive Impairment: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Exergame balance training integrates cognitive and motor challenges, potentially enhancing neuroplasticity, postural control, and gait stability in mild cognitive impairment (MCI). However, whether modulating the task difficulty of a balance-based exergame training may influence posture- and gait-related outcomes remains unknown. OBJECTIVE: We compared balance and gait improvements across exergame training groups performing exercise with different difficulty levels and a Wii Fit group in adults with MCI. METHODS: This 4-armed, parallel design, double-blinded, randomized clinical trial included 97 participants with MCI (Montreal Cognitive Assessment score=18-25). Participants were convenience-sampled from the Railway General Hospital, Rawalpindi, Pakistan, and randomized to one of 4 intervention groups: low-difficulty, moderate-difficulty, high-difficulty exergame training or a Wii Fit training group. Each participant completed 24 sessions (40 min, 3/week) supervised by physical therapists. Gait and balance were assessed using time up and go (TUG), cognitive time up and go (C-TUG), and the Gait & Balance mobile app at baseline and after 4 and 8 weeks. Although the calculated sample size was 80, 97 were recruited to offset attrition. Eighty-seven participants completed the study (94% adherence) (attrition: low-difficulty 1, moderate 3, high 2, Wii Fit 2; 10% total). Data were analyzed using mixed-model analysis of covariance with baseline values as covariates to assess time×group interactions. Bonferroni-adjusted post hoc comparisons revealed between-group differences. RESULTS: High-difficulty training showed the greatest TUG gains (-0.71, SD 0.32; P=.03, anteroposterior (AP) steadiness with eyes open (EO) on firm surface (0.04, SD 0.02; P=.04), step time variability head forward (HF; 0.06, SD 0.09; P=.02), walking speed HF (0.08, SD 0.04; P=.05), step time head turn (HT; -0.04, SD 0.02; P=.04), step time variability HT (-0.35, SD 0.09; P<.001), step length variability (-0.27, SD 0.13; P=.04), and walking speed HT (0.09, SD 0.04; P=.01) versus Wii Fit. Moderate-difficulty training improved AP steadiness EO firm (0.05, SD 0.02; P=.03) and reduced step time variability HT (-0.26, SD 0.09; P=.01). Low-difficulty training improved C-TUG (-1.61, SD 0.63; P=.01), AP steadiness EO firm (0.05, SD 0.02; P=.03), step time variability HF (-0.20, SD 0.09; P=.03), step time variability HT (-0.25, SD 0.09; P=.01), step length variability (-0.31, SD 0.12; P=.014), and walking speed HT (0.11, SD 0.04; P=.03). No significant differences observed between exergame difficulty groups (P>.05). CONCLUSIONS: Balance-based exergame training improves balance and gait in adults with MCI, with no significant differences across difficulty levels, while the high- and low-difficulty training outperformed Wii Fit in several outcomes. High-difficulty training yielded the most consistent improvements in TUG, postural steadiness, gait variability, and walking speed. These results support graded cognitive-motor exergaming as an effective strategy for enhancing postural control and walking stability in MCI, potentially aiding fall prevention and mobility preservation in aging populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT04959383; https://clinicaltrials.gov/study/NCT04959383.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".