Xbox 360 Kinect Cognitive Games Improve Slowness, Complexity of EEG, and Cognitive Functions in Subjects with Mild Cognitive Impairment: A Randomized Control Trial
Bibliographic record
Abstract
OBJECTIVES: Physical activity and cognitive training are effective to enhance cognition in older patients with mild cognitive impairment (MCI). Xbox 360 Kinect cognitive games are a combination of physical activity and cognitive training. The objective of this study was to determine the short- and long-term effects of Xbox 360 Kinect cognitive games on slowness and complexity of electroencephalography (EEG) and cognitive functions in older subjects with MCI. MATERIALS AND METHODS: A clinical trial was conducted on 44 MCI subjects. Both males and females were randomized into experimental group (participated in Xbox 360 Kinect cognitive games) and control group (range of motion exercises only and no Xbox 360 Kinect cognitive games). Subjects were assessed before and after one session of game intervention for short-term effects and after 6 weeks for long-term effects. The outcome measures were the mini-mental state examination (MMSE), Montreal cognitive assessment scale (MoCA), trail making test (TMT) A and B, and slowness and complexity of EEG. RESULTS: After one session of game intervention, delta (0.704 ± 0.025; P = 0.013), theta (0.128 ± 0.009; P = 0.00127) waves, and complexity of EEG (0.642 ± 0.042; P = 0.008) significantly improved, in eyes closed state. Whereas after 6 weeks intervention of games, delta (0.673 ± 0.029; P = 0.013), theta (0.129 ± 0.013; P = 0.002), beta2 waves (0.044 ± 0.009; P = 0.046), complexity of EEG (0.051 ± 0.042; P = 0.016), MMSE (26.25 ± 0.347 vs. 23.722 ± 0.731; P = 0.003), MoCA (25.65 ± 0.310 vs. 22.00 ± 0.504; P = 0.0001), TMT-A (1.429 ± 0.234 vs. 2.225 ± 0.259; P = 0.028), and TMT-B (2.393 ± 0.201 vs. 3.780 ± 0.195; P = 0.0001) improved significantly. These changes were not observed in the control group. CONCLUSION: Xbox 360 Kinect games showed beneficial effects after short- and long-term intervention on MCI subjects. These games can serve as potential therapeutic candidates for MCI.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".