Smart Steps to Growth: Unleashing AI for Assessing Motor Skills in School Children

Chang Gung Medical Foundation

Status: Active, not recruiting

Conditions: Developmental Coordination Disorder; AIMAS

Study type: Observational

Funder types: Other

Identifiers

NCT07083726

202401852B0

Details and patient eligibility

About

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.

Enrollment: 250 estimated patients

Sex: All

Ages: 6 to 12 years old

Volunteers: No Healthy Volunteers

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.

Trial design

250 participants in 2 patient groups

Typically Developing Children

Description:

School-age children aged 6 to 12 years who do not have a diagnosis of developmental coordination disorder (DCD).

Developmental Coordination Disorder children

Description:

School-age children aged 6 to 12 years who have a confirmed diagnosis of DCD.