Commercial Gaming Devices for Stroke Upper Limb Rehabilitation: A Systematic Review
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Rehabilitation using commercial gaming devices is a new concept for stroke care. Commercial gaming devices such as Nintendo Wii or Sony PlayStation encourage high repetition of arm movements and are being introduced into some clinical settings. The evidence base for gaming use in rehabilitation is growing rapidly and there is a need to systematically synthesise research. Our review aims to integrate evidence on how gaming is being used, explore patient/therapist experience and synthesise evidence of effectiveness. SUMMARY OF REVIEW: An integrative systematic review was undertaken searching Cochrane Central Register of Controlled Trials (2013), Medline (2013), Embase (2013) and twelve additional databases. Two review authors independently selected studies based on pre-defined inclusion criteria, extracted data and assessed risk of bias. Nineteen studies including 215 patients met inclusion criteria. Studies were typically small scale feasibility studies using a range of research designs, limiting the ability to reach generalised conclusions. Results have been tabulated (activities of daily living, upper limb function/ movement) and qualitative themes identified. Findings suggest that most patients enjoy using commercial gaming and can tolerate 180 mins per week without significant adverse effects. A trend towards improvement was noted for upper limb function/ movement. Few studies recorded outcomes related to activities of daily living or focused on understanding patients' experiences of this intervention. CONCLUSION: Commercial gaming can provide high intensity upper limb practice however there is insufficient high quality evidence to reach generalisable conclusions about risks or benefits on activities of daily living or upper limb function/movement.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".