The purpose of this study is to develop an AI-based automated motor function assessment system (AIMAS) to improve early identification of developmental coordination disorder (DCD) in school-age children. The main hypothesis for this study is: Integrating AI into motor skill assessments will enhance the reliability, validity, efficiency, and accuracy of evaluating motor performance in children aged 6 to 12.
Study Type
OBSERVATIONAL
Enrollment
250
Chang Gung Memorial Hospital
Taoyuan District, Taiwan
Motor Function Assessment Score
AI-based Motor Function Test (Higher scores indicate better motor performance and lower risk of Developmental Coordination Disorder (DCD).)
Time frame: Baseline
DCD Risk Classification
AIMAS System Classification (System's ability to identify children at risk of DCD, compared to clinical diagnosis.)
Time frame: Baseline
The Bruininks-Oseretsky Test of Motor Proficiency, Second Edition (BOT-2)
Time frame: baseline
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.