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ML-Based Multi-Sensor Fall Risk Screening in DMD

ML-Based Multi-Sensor Fall Risk Screening in DMD

Recruiting
10-30 years
All
Phase N/A

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Overview

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.

Eligibility

Inclusion Criteria:

  1. Individuals with a confirmed genetic diagnosis of Duchenne Muscular Dystrophy (DMD)
  2. Age over 10 and under 30 years
  3. Brooke Scale score between 2 and 5
  4. Manual muscle test grade below 3 for shoulder abduction muscles

Exclusion Criteria:

  1. Individuals who are unable or unwilling to provide informed consent
  2. Brooke Scale score of 1 or 6
  3. Individuals with cognitive impairments that significantly limit their ability to participate in assessments

Study details
    DMD

NCT07015632

Seoul National University Hospital

15 October 2025

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