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Record W4416738118 · doi:10.2196/74314

Evaluating the Effectiveness of Immersive Virtual Reality Rehabilitation Games With Enhanced Visual Training for Hand Motor Function Improvement Using Electromyography: Randomized Controlled Trial

2025· article· en· W4416738118 on OpenAlexvenueno aff
Faisal Amin, Asim Waris, Muhammad Jawad Khan, Muhammad Adeel Ijaz, Hammad Nazeer, Syed Omer Gilani, Fawwaz Hazzazi, Umer Hameed Shah

Bibliographic record

VenueJMIR Serious Games · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialVirtual realityRehabilitationVisual feedbackEye–hand coordinationFunction (biology)

Abstract

fetched live from OpenAlex

Background: Hand motor dysfunction greatly reduces the performance of stroke survivors. This affects their ability to perform hand motor tasks effectively. Patients receive slow interventions due to interventional limitations in stroke rehabilitation, which can pose challenges for sustaining enduring improvements. We developed immersive virtual reality (VR) games that used an innovative approach to cognitive engagement within visual training feedback for achieving long-lasting improvements. Objective: This study aimed to evaluate the effectiveness of fully immersive VR-based hand games compared with conventional physical therapy and to assess the correlations between electromyographic data and clinical outcome measures for improving hand motor function in patients with subacute stroke. Methods: A randomized controlled study was conducted among 52 patients with subacute stroke who met the inclusion criteria. These patients were equally allocated to an experimental group (n=26) and a control group (n=26). The experimental group received both fully immersive VR-based hand game therapy and conventional physical therapy, whereas the control group received only conventional physical therapy. Owing to the nature of the intervention, the study was unblinded, and both therapists and patients were aware of the intervention. Both groups participated in intervention sessions 4 days a week for 6 weeks (24 sessions in total). Moreover, both groups underwent 2 weeks of follow-up. Clinical outcome measures, including the Fugl-Meyer Assessment-upper extremity (FMA-UE), Action Research Arm Test (ARAT), and Box and Block Test (BBT), were used to assess motor recovery and functional performance. The minimal clinically meaningful difference (MCID) was used for comparing clinical outcome measures to examine clinically meaningful improvements. Furthermore, the correlation between electromyography data and clinical outcome measures, and the weekly progression in movement performance were evaluated to identify improvements in hand motor function. Results: After the intervention, there were significant differences in FMA-UE, ARAT, and BBT scores (all P<.001) between the experimental and control groups. The MCID findings illustrated that the experimental group had clinically meaningful improvements compared to the control group. There were significant correlations between electromyography signal features and clinical outcome measures (all P<.05) in both groups after rehabilitation. However, the experimental group exhibited strong positive correlations, while the control group exhibited moderate positive correlations. At follow-up, the mean movement accuracy was notably higher in the experimental group than in the control group (mean 83.59%, SD 1.1% vs mean 79.20%, SD 0.8%), indicating that hand motor function was effectively sustained through the use of the VR-based intervention in the experimental group. Conclusions: The findings of this study revealed that VR-based hand games with enhanced visual training feedback substantially improved hand motor function in patients with subacute stroke.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.361
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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