Prediction of ADHD in Children Using Pedobarographic and Postural Data
Recruiting · NCT07180758 · Observational (researchers observe without assigning treatment) · Lead sponsor: Biruni University
View the official record on ClinicalTrials.gov →What this trial is about
The aim of this study is to investigate the potential of postural control and plantar pressure data in predicting Attention Deficit Hyperactivity Disorder (ADHD) in middle school students using machine learning methods. A total of 100 students will participate, including those identified with symptoms of ADHD and healthy controls. Participants will undergo non-invasive biomechanical assessments, including pedobarographic foot pressure measurement and mobile posture analysis. Behavioral data will be collected using DSM-IV-based rating scales developed by Atilla Turgay, completed separately by parents, teachers, and caregivers. All data will be used to develop predictive models using algorithms such as random forest, logistic regression, and support vector machines. The study is observational and cross-sectional.
Who can take part
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 it is running
1 location listed.
- Biruni University, Faculty of Health Sciences - Istanbul, Turkey (Türkiye)