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.

Inclusion Criteria:

• Children aged 6 to 12 years.
• For DCD group: formal diagnosis of Developmental Coordination Disorder (DCD).
• For typically developing group: no disabilities or developmental delays.

Exclusion Criteria:

• Acute illnesses (e.g., pneumonia, upper gastrointestinal hemorrhage).
• Significant developmental delays or disabilities.
• Genetic diseases or disorders.
• Neurological disorders or injuries.

The study will recruit 250 school-age children, aged 6 to 12, including 170 typically developing children and 80 children with DCD.