Serious Game for Fine Motor Control Rehabilitation for Children With Epileptic Encephalopathy: Development and Usability Study
Bibliographic record
Abstract
BACKGROUND: Epileptic encephalopathy (EE) is defined as the presence of frequent epileptiform activity that adversely impacts development, typically causing the slowing or regression of developmental skills, and is usually associated with frequent seizures. One of the main disturbances in EE is in the coordination of the upper extremities and hands. Traditional rehabilitation for this type of pathology focuses on the alleviation of gross or fine motor disability. In the last few years, the use of low-cost devices together with customized serious games has shown improvements in motor disorders and enrichments in activities of daily living. OBJECTIVE: This study aims to explore the feasibility of a new serious game for improving fine motor control in children with EE. METHODS: The participants were 4 children with EE (male: n=2, 50%; female: n=2, 50%) who were classified as belonging to level 1 in the Gross Motor Classification System. The children were tested over 10 sessions during the intervention period (before and after treatment). The clinical tests performed were the Bruininks-Oseretsky Test of Motor Proficiency, 2nd edition and Pittsburgh Rehabilitation Participation Scale. The subscales of the Bruininks-Oseretsky Test of Motor Proficiency, 2nd edition were fine motor precision, fine motor integration, manual dexterity, and upper-limb coordination. At the end of the first session, we used the User Satisfaction Evaluation Questionnaire to analyze user satisfaction. RESULTS: The significance outcomes for a Student t test (1-tailed) were as follows: P=.009 for fine motor precision, P=.002 for fine motor integration, P=.56 for manual dexterity, and P=.99 for upper-limb coordination. The participation rate as measured using the Pittsburgh Rehabilitation Participation Scale was between good and very good, which means that, based on the therapist's evaluation, interest, independence, and motivation were achieved by each participant. The mean User Satisfaction Evaluation Questionnaire score was close to 30, which is the maximum value. CONCLUSIONS: The results support the use of the proposed serious game as a complement in therapeutic sessions during the rehabilitation processes for children with EE. Significant improvements in fine motor control and activities of daily living revealed that the proposed serious game is beneficial for fine motor disorders of this pathology.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".