Virtual Reality Exercise Improves Mobility After Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Exercise using virtual reality (VR) has improved balance in adults with traumatic brain injury and community-dwelling older adults. Rigorous randomized studies regarding its efficacy, safety, and applicability with individuals after stroke are lacking. The purpose of this study was to determine whether an adjunct VR therapy improves balance, mobility, and gait in stroke rehabilitation inpatients. METHODS: A blinded randomized controlled trial studying 59 stroke survivors on an inpatient stroke rehabilitation unit was performed. The treatment group (n=30) received standard stroke rehabilitation therapy plus a program of VR exercises that challenged balance (eg, soccer goaltending, snowboarding) performed while standing. The control group (n=29) received standard stroke rehabilitation therapy plus exposure to identical VR environments but whose games did not challenge balance (performed in sitting). VR training consisted of 10 to 12 thirty-minute daily sessions for a 3-week period. Objective outcome measures of balance and mobility were assessed before, immediately after, and 1 month after training. RESULTS: Confidence intervals and effect sizes favored the treatment group on the Timed Up and Go and the Two-Minute Walk Test, with both groups meeting minimal clinical important differences after training. More individuals in the treatment group than in the control group showed reduced impairment in the lower extremity as measured by the Chedoke McMaster Leg domain (P=0.04) immediately after training. CONCLUSIONS: This VR exercise intervention for inpatient stroke rehabilitation improved mobility-related outcomes. Future studies could include nonambulatory participants as well as the implementation strategies for the clinical use of VR. CLINICAL TRIAL REGISTRATION URL: http://www.ANZCTR.org.au/. Unique identifier: ACTRN12613000710729.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".