Evaluation of a Game-Based Mechatronic Device for Rehabilitation of Hand-Arm Function in Children With Cerebral Palsy: Feasibility Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Children with neurodevelopmental disorders, such as cerebral palsy (CP), often experience motor impairments in manual dexterity, which hinder daily tasks and social interactions. Traditional rehabilitation methods require repetitive task practice, which can be difficult for children to sustain due to low engagement. Game-based rehabilitation devices and robots offer a promising alternative by combining therapy with digital play, improving motivation and compliance. However, many systems fail to incorporate actual object manipulation, which is essential for motor learning through sensory feedback. To address this limitation, a low-cost, easy-to-use robotic manipulandum device (RMD) was developed. The RMD enables real-time object manipulation during gameplay while providing assistive force, allowing the practice of a wide range of manual dexterity skills beyond gross reaching. This system offers an engaging and effective rehabilitation approach to enhance hand function in children with CP. OBJECTIVE: This study aimed to provide evidence for the feasibility and therapeutic value of the RMD game-based exercise program for children with CP. METHODS: In total, 34 children with CP, aged 4 to 10 years, were randomly assigned to the experimental group (XG) or the control group (CG). The XG received a computer game-based exercise program using the RMD, focusing on object manipulation tasks, while the CG received task-specific training similar to constraint-induced movement therapy. Both groups received their respective therapy programs 3 times per week for 8 weeks. Semistructured interviews with parents and children, along with qualitative analysis, were conducted to evaluate their experiences with the exercise program. The following outcome measures were used: (1) the Peabody Developmental Motor Scale-2 (PDMS-2) grasping and visual-motor integration subtests and (2) the computer game-based upper extremity (CUE) assessment of manual dexterity. RESULTS: No dropouts occurred during the 8-week program. Both groups showed significant improvements in the PDMS-2 subtests (P<.001) and the CUE assessment of manual dexterity, including success rates (tennis ball: P=.001; cone: P<.001; medicine ball: P=.001; and peanut ball: P<.001) and movement errors (tennis ball: P=.01; cone: P<.001; medicine ball: P=.04; and peanut ball: P<.001). The XG outperformed the CG, showing greater improvements in PDMS-2 grasping (P=.002) and visual-motor integration (P=.01). In the CUE assessment, the XG demonstrated higher success rates (medicine ball: P=.001 and peanut ball: P=.02) and fewer movement errors (cone: P<.001). Parents reported an increase in the children's independence in daily tasks. CONCLUSIONS: This study demonstrates the feasibility, acceptability, and positive outcomes of the RMD game-based exercise program for improving hand function in children with CP. The findings support further research and development of computer game-assisted rehabilitation technologies. TRIAL REGISTRATION: Clinical Trials Registry - India CTRI/2021/07/034903; https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=NTc4ODU.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".