AI-Based Digital Therapeutics vs. Traditional Schroth Exercises for Adolescent Idiopathic Scoliosis

NCT07341633 | Active Not Recruiting

• 1 other identifier: GWCMC-2025-497A01
• Study Type: interventional
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Adolescent Idiopathic Scoliosis (AIS)

Keywords

Digital Therapeutics; Artificial Intelligence; Schroth Method; Tele-rehabilitation; Computer Vision; Scoliosis

Outcome Measures

Primary Outcomes (1)

• Absolute Change in Major Curve Cobb Angle

  Measured on standardized standing posteroanterior full-spine radiographs. The Cobb angle is the angle formed between the upper endplate of the most tilted upper vertebra and the lower endplate of the most tilted lower vertebra. Measurements are performed in degrees by independent radiologists who are blinded to group allocation. A negative value indicates a reduction (improvement) in the spinal curve.

  Baseline, 3 months, and 6 months

Secondary Outcomes (4)

• Treatment Adherence Rate

  Baseline, 3 months, and 6 months

• Change in Angle of Trunk Rotation (ATR)

  Baseline, 3 months, and 6 months

• Change in Quality of Life (SRS-22r Score)

  Baseline, 3 months, and 6 months

• Change in Trunk Appearance Perception (TAPS)

  Baseline, 3 months, and 6 months

Study Arms (2)

Standard Outpatient Schroth Therapy

ACTIVE COMPARATOR

Participants receive standard conservative care based on Schroth Best Practice guidelines. This involves an initial 60-minute comprehensive evaluation, followed by a personalized home exercise program (30 minutes daily). Participants attend monthly supervised sessions at the outpatient clinic for manual prescription adjustments by a certified therapist .

Behavioral: Standard Outpatient Schroth Therapy

AI-Based Digital Therapeutics (AI-DTx)

EXPERIMENTAL

Participants utilize a smartphone application to capture standardized photos every two weeks. An AI algorithm (MediaPipe-based) processes these images to classify curve patterns and assign personalized exercise modules. The system uses a "Human-in-the-Loop" workflow where a Clinical Research Assistant verifies the AI-generated prescription before release. Dosing intensity is adaptively adjusted based on metric changes.

Device: AI-Based Digital Therapeutic System

Interventions

Standard Outpatient Schroth Therapy BEHAVIORAL

Standard conservative management based on the SOSORT and Schroth Best Practice guidelines. Participants undergo an initial 60-minute comprehensive evaluation and education session. The intervention consists of a daily home exercise program (30 minutes/day) and mandatory monthly face-to-face supervised sessions at the outpatient clinic, where a certified therapist manually adjusts the exercise prescription based on clinical progression .

Standard Outpatient Schroth Therapy

AI-Based Digital Therapeutic System DEVICE

A smartphone-based digital therapeutic application that utilizes computer vision (MediaPipe Framework) to capture and analyze patient posture bi-weekly. The system employs a hierarchical triage logic to classify curve patterns and assign personalized Schroth-based exercise modules. It features a "Human-in-the-Loop" safety protocol where a Clinical Research Assistant validates the AI-generated prescription before release. The exercise dosing (intensity and props) is adaptively adjusted based on the calculated metric changes (NSI) every two weeks .

AI-Based Digital Therapeutics (AI-DTx)

Eligibility Criteria

• Age: 10 Years - 18 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64)

You may qualify if:

• Diagnosis of Adolescent Idiopathic Scoliosis (AIS).
• Age between 10 and 18 years (inclusive).
• Cobb angle of the major curve between 10° and 30°.
• Risser sign 0-2 (indicating skeletal immaturity).
• Ability to operate a smartphone and follow instructions for the digital therapeutic application.
• Patient and legal guardian provide written informed consent.

You may not qualify if:

• Non-idiopathic scoliosis (e.g., congenital, neuromuscular, or syndromic etiology).
• History of prior spinal surgery or currently scheduled for surgery.
• Contraindications to exercise therapy (e.g., cardiac or respiratory insufficiency).
• Severe cognitive or psychiatric disorders that prevent compliance with the protocol.
• Currently receiving other scoliosis-specific treatments (e.g., bracing) outside of the study protocol (unless stratified).

Sponsors & Collaborators

• Jinan University Guangzhou: lead
• Guangzhou Women and Children's Medical Center: collaborator

Study Sites (1)

Guangzhou Women and Children's Medical Center

Guangzhou, Guangdong, 510623, China

Location

MeSH Terms

Conditions

Scoliosis

Condition Hierarchy (Ancestors)

Spinal Curvatures; Spinal Diseases; Bone Diseases; Musculoskeletal Diseases

Study Officials

• Lili Shu, MD

  Guangzhou Women and Children's Medical Center

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Masking Details: Due to the visible nature of the exercise intervention, it is not possible to blind participants or care providers. To minimize detection bias, the primary outcome (Cobb angle) will be assessed by independent radiologists who are strictly blinded to group allocation and the timing of the radiographs.
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Lecturer

Model Details: A parallel-group, single-blind randomized controlled trial comparing an AI-based digital therapeutic intervention against a standard care control group.

Study Record Dates

• First Submitted: January 6, 2026
• First Posted: January 14, 2026
• Study Start: February 1, 2026
• Primary Completion (Estimated): January 1, 2028
• Study Completion (Estimated): January 1, 2028
• Last Updated: April 23, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF
• Time Frame: Beginning 9 months after publication of the primary results article and ending 36 months thereafter.
• Access Criteria: Access will be granted to qualified researchers whose proposed use has been approved by an independent review committee for the purpose of individual participant data meta-analyses or methodologically sound secondary analyses. Requests should be directed to the corresponding author (penny@link.cuhk.edu.hk) and must include a detailed research proposal, a statistical analysis plan, and evidence of ethical approval from the requester's institution. Data will be shared through a secure data transfer platform following the execution of a signed Data Use Agreement.

Locations

CN (1)