Virtual Reality in Stroke Rehabilitation: A Systematic Review of its Effectiveness for Upper Limb Motor Recovery
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Metaresearch, Meta-epidemiology (narrow)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Systematic reviewConsensus signal: Systematic review
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.073
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.340 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
PURPOSE: It is estimated that 50% to 75% of individuals who experience a stroke have persistent impairment of the affected upper limb (UL). There is a need to identify the best training strategies for retraining motor function of the UL. One intervention showing promise is virtual reality (VR), using either immersive or nonimmersive technology. Before recommending VR for use in clinical practice, it is important to understand the evidence regarding its effectiveness. METHOD: Two questions about the effectiveness of VR for UL rehabilitation in stroke were posed: (1) Is the use of immersive VR more effective than conventional therapy or no therapy in the rehabilitation of the UL in patients with hemiplegia? (2) Is the use of nonimmersive VR more effective than conventional therapy or no therapy in the rehabilitation of the UL in patients with hemiplegia? RESULTS: There is level 1b evidence suggesting an advantage to training in immersive VR environments versus no therapy in UL rehabilitation, and level 5 evidence for training in immersive VR versus conventional therapy. There is level 4 evidence showing conflicting results for training in nonimmersive VR versus no therapy, and level 2b evidence for training in nonimmersive VR versus conventional therapy. CONCLUSION: The current evidence on the effectiveness of using VR in the rehabilitation of the UL in patients with stroke is limited but sufficiently encouraging to justify additional clinical trials in this population.
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.
The record
- Venue
- Topics in Stroke Rehabilitation
- Topic
- Stroke Rehabilitation and Recovery
- Field
- Medicine
- Canadian institutions
- Centre for Interdisciplinary Research in RehabilitationMcGill University
- Funders
- Canada Research ChairsMcGill University
- Keywords
- RehabilitationVirtual realityPhysical medicine and rehabilitationRetrainingStroke (engine)MedicinePhysical therapyPopulationOccupational therapyNeurorehabilitationIntervention (counseling)Computer scienceHuman–computer interactionNursing
- Has abstract in OpenAlex
- yes