AI-based video analysis to assess motor development in children
Official title: Development and Validation of an Artificial Intelligence-Based System for Assessing Motor Development in Children Using Video Analysis
Run by Medipol University · NCT07597356 · Data updated 2026-11-12
This study tests an AI system that watches videos of children aged 5 to 10 doing movement tasks to see if the AI’s assessments match a standard motor test.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 5 Years to 10 Years |
| Sex | All |
| Enrollment | 60 (estimated) |
| Sponsor | Medipol University Academic / other |
| Locations | 1 site (Istanbul, Beykoz) |
| Status | Recruiting |
| Started | January 1, 2026 |
| Main results expected | August 1, 2026 |
| Study ends | September 1, 2026 |
| Registry record updated | May 19, 2026 |
| Trial ID | NCT07597356 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Children aged 5 to 10 years without diagnosed neurological, developmental, or orthopedic disorders who can follow instructions and whose guardians consent.
✕Probably not a fit
Children with diagnosed neurological, developmental, or orthopedic conditions, or those unable to complete the tasks, may not benefit from this AI-based assessment approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a prospective, non-interventional study to develop and validate an AI-based system for assessing motor development in children. Participants aged 5–10 without prior neurological, developmental, or orthopedic diagnoses perform structured motor tasks while high-resolution videos are collected under controlled conditions. Computer vision extracts movement features, which are then analyzed by machine learning models to classify typical versus atypical motor development and to relate AI scores to BOT-2 SF results. The BOT-2 SF serves as the reference standard for motor performance. The study explores whether AI-derived metrics can reliably reflect motor development status as determined by established testing methods.
Why it matters
Potential benefit: If successful, the AI approach could provide a quick, objective supplementary tool for screening motor development in children.
How similar studies have gone: Prior work in AI-based movement analysis has shown promise in classification tasks, but this exact pediatric motor-development application with BOT-2 SF validation is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Children aged between 5 and 10 years * No diagnosed neurological, developmental, or orthopedic disorders * Ability to follow verbal instructions * Informed consent obtained from parents or legal guardians * No prior participation in sensory integration therapy or special education programs Exclusion Criteria: * Diagnosed neurological, developmental, or orthopedic conditions (e.g., autism spectrum disorder, cerebral palsy, epilepsy) * Visual or hearing impairments affecting task performance * Severe attention or behavioral problems preventing test completion * Physical limitations preventing participation in motor tasks
Where it's running
-
Istanbul Medipol University
Istanbul, Beykoz, Turkey (Türkiye) Recruiting
Study contacts
- Study coordinator: Abdullah Furkan Cangi, Msc
- Email: abdullah.cangi@medipol.edu.tr
- Phone: +90 553 622 7898
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.