Not_yet_recruitingNCT07593560

A Deep Learning-Based Approach for Early Scoliosis Detection Using mmWave Radar-Based Gait Data

Sponsor: Gebze Technical University

Trial Details

ConditionScoliosis Idiopathic Adolescent, Scoliosis
InterventionmmWave Radar Gait Assessment
StatusNot_yet_recruiting
Participants200
Est. Completion1 Dec 2027
Last Updated18 May 2026

Primary Outcome

Diagnostic Accuracy of the mmWave Radar-Based Deep Learning Model for Scoliosis Detection (AUC-ROC)

Eligibility Criteria

Inclusion Criteria

Participation Criteria: * Being between 2 and 75 years of age at the time of registration * Having applied to the pediatric orthopedics outpatient clinic for an assessment of suspected or known scoliosis * Being able to walk independently for at least 7 meters without assistive devices * Written informed consent from a parent or legal guardian * Written informed consent from the participant Exclusion Criteria: * Severe scoliosis requiring urgent surgical intervention that prevents participation in walking tasks * Refusal to give informed consent or consent

Trial Sites

Countries

Turkey (Türkiye)
View Registry Entry

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