ML-Based Multi-Sensor Fall Risk Screening in DMD

This prospective observational study aims to analyze changes in upper extremity functional movement over time in children with Duchenne Muscular Dystrophy (DMD). Thirty patients will be evaluated at three time points (baseline, 6 months, 12 months) using clinical assessments (PUL 2.0, Brooke Scale, grip strength), computer vision-based video analysis, and machine learning algorithms. The goal is to improve future upper limb evaluation methods for non-ambulatory DMD patients. The study includes safety monitoring and adheres to ethical standards, ensuring patient data confidentiality and providing compensation if adverse effects occur.