AI-Enhanced Telerehabilitation Program Using Automated Video Analysis and Personalized Feedback on Pain, Disability, Mobility, Endurance, for Chronic Non-Specific Low Back Pain in College Students: A Randomized Controlled Trial
Trial ID: NCT07145996
Status: NOT_YET_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-10-01
Completion date: 2026-09-01
Sponsor: Majmaah University
Collaborators: Galgotias University
Conditions: Non Specific Low Back Pain
Interventions: AI Based Exercises; Standard Telerehabilitation
Enrollment: 120
Age range: 18 Years - 30 Years
Sex: ALL

Summary:
This study tests whether an artificial intelligence (AI)-enhanced telerehabilitation program can effectively treat chronic non-specific low back pain in college students.

Low back pain affects 40-52% of university students due to prolonged sitting during lectures and study sessions, poor posture from laptop use, and lack of physical activity. While exercise therapy is the recommended treatment, many students cannot access traditional physiotherapy due to cost, scheduling conflicts, and location barriers.

This randomized controlled trial compares three treatment approaches: (1) AI-enhanced telerehabilitation with automated video analysis and personalized feedback, (2) standard telerehabilitation with video instructions only, and (3) usual care. The AI system uses computer vision technology (Google MediaPipe Pose) to analyze exercise videos through a standard webcam or smartphone, automatically tracking joint movements, counting repetitions, and providing real-time feedback on exercise form.

College students with chronic low back pain (lasting more than 3 months) will be randomly assigned to one of the three groups. The AI-enhanced group will receive personalized exercise programs delivered remotely, with the AI system monitoring their performance and physiotherapists providing guidance through video consultations.

The study will measure changes in pain levels, disability, physical function, trunk muscle endurance, and quality of life over 8 weeks of treatment and 3 months of follow-up. Researchers will also evaluate how well participants stick to their exercise programs and how easy the technology is to use.

This research aims to determine if AI technology can make remote physiotherapy more effective and accessible for college students, potentially transforming how young adults receive treatment for back pain and improving their long-term health outcomes.

Eligibility criteria:
Inclusion Criteria

* Age 18-30 years, currently enrolled in undergraduate or postgraduate study.
* Diagnosis of non-specific LBP for at least 3 months.
* Baseline pain intensity between 3 and 7 (NRS).
* Ability and willingness to perform prescribed exercises and participate in video conferencing.
* Access to suitable device and reliable internet.
* Informed consent obtained. Exclusion Criteria
* Specific causes of LBP (e.g., fracture, tumor, infection, inflammatory disease).
* Recent spinal surgery or confirmed disc herniation (within past year).
* Neurological deficits or severe comorbid conditions contraindicating exercise.
* Pregnancy or current participation in another structured LBP program.
* BMI ≥ 35 kg/m² (could impair AI pose detection).
* Inability to understand English instructions or complete measures.

Outcomes:
Numerical pain rating scale