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This randomized controlled trial (RCT) evaluates the efficacy of a novel Artificial Intelligence (AI)-based digital therapeutic system compared to traditional outpatient Schroth exercises for the treatment of Adolescent Idiopathic Scoliosis (AIS). The intervention utilizes a smartphone application with computer vision technology to perform remote, personalized posture analysis and generate adaptive exercise prescriptions. The study aims to determine if this "Human-in-the-Loop" AI model demonstrates superior clinical outcomes in controlling spinal curve progression and improving treatment adherence compared to standard conservative care over a 6-month period.
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Background: Adolescent Idiopathic Scoliosis (AIS) requires long-term conservative management to prevent curve progression. While Physiotherapeutic Scoliosis Specific Exercises (PSSE), such as the Schroth method, are the gold standard, their efficacy is often limited by accessibility barriers and suboptimal adherence.
Study Design: This is a parallel-group, single-blind randomized controlled trial. A total of 300 eligible adolescents (aged 10-18, Cobb angle 10-30°, Risser sign 0-2) will be randomized in a 1:1 ratio into an Intervention Group or a Control Group.
Interventions:
Intervention Group (AI-DTx): Participants utilize a smartphone application to capture standardized photos every two weeks. An AI algorithm (based on MediaPipe) extracts skeletal landmarks to classify curve patterns and assign personalized exercise modules. The system features a "Check-and-Adjust" matrix to adapt exercise intensity based on metric changes. A Clinical Research Assistant (Human-in-the-Loop) verifies all prescriptions for safety before release.
Control Group (Standard Care): Participants receive standard outpatient Schroth therapy, involving daily home exercises and monthly supervised clinic visits, following SOSORT guidelines.
Objectives: The primary objective is to evaluate the absolute change in the major curve Cobb angle from baseline to six months. Secondary outcomes include the Angle of Trunk Rotation (ATR), trunk appearance perception (TAPS), quality of life (SRS-22r), and adherence rates. The study hypothesizes that the AI-driven intervention will demonstrate superior efficacy and adherence compared to traditional outpatient care.
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300 participants in 2 patient groups
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Rui Si Ma, PhD
Data sourced from clinicaltrials.gov
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