Predicting ADHD in middle-school children from foot pressure and posture measurements

Prediction of Attention Deficit Hyperactivity Disorder (ADHD) in Middle School Children Using Machine Learning With Pedobarographic Data

Observational Biruni University · NCT07180758

Researchers will try to see if foot pressure and posture measurements can help predict ADHD in middle-school-aged children.

Quick facts

Study typeObservational
Enrollment100 (estimated)
Ages10 Years to 14 Years
SexAll
SponsorBiruni University Academic / other
Locations1 site (Istanbul)
Trial IDNCT07180758 on ClinicalTrials.gov

What this trial studies

This observational cross-sectional project will enroll about 100 children aged 10–14 (approximately 50 with clinical ADHD and 50 healthy controls) from middle schools in the Eyüpsultan district of Istanbul. Participants will undergo non-invasive biomechanical testing including static and dynamic pedobarography, mobile posture analysis, balance tests (Flamingo and Y Balance), and anthropometric measurements, while behavioral ratings based on DSM-IV scales are collected from parents, teachers, and caregivers. Physical activity will be recorded with the IPAQ-SF and foot posture assessed with the Foot Posture Index. Collected features will be used to train and compare machine-learning classifiers such as random forest, logistic regression, and support vector machines to develop predictive models for ADHD.

Who should consider this trial

Good fit: Ideal participants are 10–14-year-old middle-school students enrolled full-time in Eyüpsultan schools who have parental consent and age-appropriate motor development, including both children with clinically diagnosed ADHD and healthy controls.

Not a fit: Children who have had lower-extremity or spinal orthopedic surgery, congenital or acquired neuromuscular disorders, major visual or hearing impairments, systemic diseases, or who live outside the study area are unlikely to benefit or be eligible.

Why it matters

Potential benefit: If successful, this work could provide a simple, non-invasive set of objective measurements to help screen or support diagnosis of ADHD in school-aged children.

How similar studies have performed: Previous research has reported differences in postural control and sway in children with ADHD, and some small machine-learning studies using movement or posture data have shown promising but preliminary predictive results.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Students attending a middle school located in Eyüpsultan district
* Informed consent obtained from their parents
* Students enrolled in full-time education
* Children with age-appropriate motor development skills.

Exclusion Criteria:

* Children who have undergone orthopedic interventions due to lower extremity or spinal deformities
* Children with congenital or acquired neuromuscular disorders
* Children with significant visual or auditory impairments
* Children with systemic diseases

Where this trial is running

Istanbul

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Attention Deficit Hyperactivity DisorderAttention Deficit Disorder with HyperactivityArtificial IntelligencePostureMachine Learningchild
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.