Constraint Induced Movement Therapy Camp for Children with Hemiplegic Cerebral Palsy Augmented by Use of an Exoskeleton to Play Games in Virtual Reality
Bibliographic record
Abstract
Aim To determine the acceptability and effects of a pediatric constraint induced movement therapy (P-CIMT) camp for children with hemiplegic cerebral palsy (hCP) augmented by use of an exoskeleton to play games in virtual reality (VR).Method 31 children with hCP attended a P-CIMT camp 6 hours per day for 10 days over 2 successive weeks (60 hours) that included 30 minutes of unilateral training with the Hocoma Armeo®Spring Pediatric that combines the assistance of an exoskeleton and VR games. The primary outcome measure was the Assisting Hand Assessment (AHA); secondary outcome measures were the Melbourne Assessment of Uni-lateral Hand Function (MUUL), and the Canadian Occupational Performance Measure (COPM). Assessments were completed at pre-intervention, post-intervention, and 6 months following intervention.Results Participants demonstrated clinically and statistically significant improvement in bimanual performance (AHA) (p < .001) and COPM Performance (p < .001) and Satisfaction with performance (p < .001). Improvement in unilateral performance (MUUL) was statistically (p < .001) but not clinically significant.Conclusions A P-CIMT camp augmented by the Hocoma Armeo®Spring Pediatric was feasible and accepted by participants. Bimanual hand function and occupational performance improved immediately following intervention, and the treatment effects persisted 6 months following intervention.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".