A COMPARATIVE STUDY ON THE EFFECTIVENESS OF VIRTUAL REALITY VERSUS CONVENTIONAL EXERCISE THERAPY FOR REHABILITATION OF UPPER LIMB IN STROKE SURVIVORS
Bibliographic record
Abstract
Background: The most prevalent dysfunction following a stroke is weakness or paralysis, which often leads to upper limb impairments, Limiting independence in daily activities. Virtual Reality has emerged as recent treatment approach in stroke rehabilitation. VR therapies give stroke survivors the rare chance to engage in a rich environment while receiving scalable, structured training Opportunities reinforced by multimodal feedback to improve neuroplasticity and skill acquisition via repeated practice. To Aim: determine the effect of Virtual Reality-based therapy along with Conventional exercises in improving upper limb motor functions, Cognition deficits, Depression, and Quality of life in stroke survivors. This was randomized control trial, inv Methods and Material: olved 18 Stroke survivors in Sub-Acute stage. All Participants were randomly divided in to Experimental and Control group. All participants in Experimental group received VR- based Exercise therapy along with Conventional Exercise therapy and Control group participant received conventional exercise therapy only 5 times per week for 4 weeks. Data were collected at day 0 and at day 30th by using the outcome measure tools like Fugl Meyer Assessment-UA, Montreal Cognitive, Assessment scale, Beck depression inventory and Stroke impact scale. The analysis of the data was done by using SPSS Software. Significant improvements was observed in Fugl Mayer-UL (p < 0.05), MoCA Result: (p < 0.05), scores, Beck Depression inventory (p < 0.05) and in stroke impact scale Strength, Memory and thinking, ADL/IADL, Communication, Emotion, Hand functions, Participation (p <0.05) domains demons. VR-based exercise therapy along with conventiona Conclusion: l Physiotherapy shows potential to improve motor and cognitive functions in stroke survivors
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".