AR Support System for Therapy in 3 to 8-Year-Old Children with Altered Fine Motor Skills
Bibliographic record
Abstract
In this project, an augmented reality (AR) system was designed and developed to contribute to therapy in children from ages 3 to 8 who suffer from fine motor skills disorder or seek to improve their skills during their neurodevelopment.The system was designed in the Unity engine along with a Leap Motion sensor so that the kids' hands can interact with scenarios created in the platform.The construction of the system followed the respective phases that describe the cascade methodology for the development of software systems, including the study of requirements and use cases.Additionally, it is intended that the progress of the child is tracked when he/she is performing a set of activities to develop fine motor skills.The Feine Motonik "FeMo" built module, has an 88.9% usability according to the study carried out in this article, which contemplates the test phase with the objective users who describe the situation of disorders in fine motor skills.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".