A Deep Learning-Based Approach for Early Scoliosis Detection Using mmWave Radar-Based Gait Data
Sponsor: Gebze Technical University
Trial Details
| Condition | Scoliosis Idiopathic Adolescent, Scoliosis |
| Intervention | mmWave Radar Gait Assessment |
| Status | Not_yet_recruiting |
| Participants | 200 |
| Est. Completion | 1 Dec 2027 |
| Last Updated | 18 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
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