Prediction of ADHD in Children Using Pedobarographic and Postural Data
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age10-14
SponsorBiruni University
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
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.
Disqualifiers
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
Trial population
Children aged 10 to 14 years, including both those diagnosed with ADHD and healthy peers, attending a middle school in the Eyüpsultan district. Participants will be selected based on their eligibility criteria and categorized accordingly.
Trial design
Design model
Case-control
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
100 Participants
are grouped into 2 trial groupsGroup A: ADHD Group
Group B: Healthy Control Group
Trial outcomes
Primary outcomes
1
Prediction of ADHD Diagnosis Using Biomechanical and Postural Parameters
Diagnostic accuracy (sensitivity, specificity, overall accuracy, AUC) of a machine learning model developed using postural, balance, pedobarographic, and anthropometric parameters will be evaluated in distinguishing ADHD and control children.
Time frame
Baseline (Single assessment session)Secondary outcomes
1
Postural Assessment via Mobile Posture App
Postural alignment will be assessed using the Mobile Posture App in four views (frontal, sagittal-right, sagittal-left, and posterior). The application provides angular deviations in degrees (°) for multiple anatomical landmarks, including: Frontal view: ears, shoulders, hips, and trunk inclination (tilt from vertical midline). Sagittal views (right and left): trunk inclination (forward/backward tilt relative to vertical). Posterior view: ears, shoulders, hips, and trunk inclination (tilt from vertical midline). Higher values indicate greater postural deviation or asymmetry, while lower values indicate closer alignment to neutral posture.
Time frame
Baseline2
Postural Assessment - New York Posture Rating Test (NYPRT)
Postural alignment will be evaluated with the New York Posture Rating Test. The test yields a total score from 13 to 65 based on visual ratings of multiple body segments in standing posture. Higher scores indicate better postural alignment; lower scores indicate poorer posture.
Time frame
Baseline3
Plantar Pressure Distribution
Plantar pressure distribution will be assessed using the Metisens Static Pedobarography system. The outcome is expressed as % of total load distributed across left vs right foot and forefoot, midfoot, hindfoot regions. Higher asymmetry indicates poorer postural control.
Time frame
Baseline4
Foot Posture Assessment - Foot Posture Index (FPI-6) Total Score
Foot posture will be assessed using the Foot Posture Index (FPI-6), which evaluates six criteria including talar head palpation, supra/inframalleolar curvature, calcaneal frontal plane position, talonavicular bulging, medial arch height, and forefoot abduction/adduction. Each item is scored on a 5-point scale (-2 to +2), yielding a total score from -12 to +12. Higher positive scores indicate increased pronation. Negative scores indicate supination. Scores around 0 indicate neutral foot posture.
Time frame
BaselineSponsors and contacts
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Source ClinicalTrials.gov