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.

NCT07145996 | Not Yet Recruiting DMC

• 1 other identifier: GALGOTIASUNIVERSITY
• Study Type: interventional
• Target: 120
• Locations: 0 countries
• Sites: N/A

Brief 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.

Conditions

Non Specific Low Back Pain

Keywords

back pain; exercise; young adults; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Numerical pain rating scale

  A unidimensional measure of pain intensity in which participants rate their average low back pain over the past week on an 11-point scale from 0 ("no pain") to 10 ("worst imaginable pain"). The NRS is valid, reliable, and sensitive to clinical change in chronic low back pain populations.

  From enrollment to the end of treatment at 6 week and 3 months

Secondary Outcomes (3)

• Roland-Morris Disability Questionnaire (RMDQ)

  From enrollment to the end of treatment at 6 weeks and 3 months

• Timed Up and Go (TUG) Test

  From enrollment to the end of treatment at 6 weeks and 3 months

• Prone Plank Test

  From enrollment to the end of treatment at 6 weeks and 3 months

Study Arms (3)

AI-Enhanced Telerehabilitation

EXPERIMENTAL

Participants receive personalized exercise programs delivered through a custom telerehabilitation platform incorporating AI-based movement analysis using Google MediaPipe Pose computer vision technology. The system monitors exercise performance through participants' webcams or smartphones, providing real-time feedback on form, automatically counting repetitions, measuring hold times, and flagging technique errors. AI-generated performance data is reviewed by physiotherapists who provide personalized corrective guidance through scheduled video consultations. Exercises focus on flexibility, core stability, and functional strength targeting chronic non-specific low back pain. The intervention combines objective AI monitoring with human therapeutic guidance to optimize exercise adherence and technique.

Other: AI Based Exercises

Exercise-Only Telerehabilitation

ACTIVE COMPARATOR

Participants receive structured exercise programs delivered via pre-recorded video instructions without AI monitoring or automated feedback. This represents current standard telerehabilitation practice, with periodic physiotherapist consultations conducted through video conferencing sessions. Exercise programs include the same flexibility, core stability, and functional strength components as the AI-enhanced group, but without objective movement analysis or real-time form correction. Therapists rely on visual observation during video sessions and participant self-reports to monitor progress and provide guidance. This arm serves as an active control to isolate the specific effects of AI-enhanced monitoring and feedback.

Other: Standard Telerehabilitation

Usual Care

NO INTERVENTION

This control intervention represents standard medical care typically provided to college students with chronic non-specific low back pain. Participants receive general advice on activity modification, recommendations for over-the-counter pain medications (NSAIDs, acetaminophen), basic exercise suggestions, and routine follow-up appointments as clinically indicated. No structured exercise program, telerehabilitation platform, or specialized physiotherapy intervention is provided. Participants may seek additional healthcare services as they normally would, including visits to primary care physicians, specialists, or other healthcare providers. This arm serves as a control group to evaluate the effectiveness of both telerehabilitation interventions against current standard medical management practices.

Interventions

AI Based Exercises OTHER

This intervention combines structured exercise therapy with artificial intelligence-powered movement analysis using Google MediaPipe Pose technology. Participants perform prescribed exercises (flexibility, core stability, functional strength) while a computer vision system analyzes their movements through standard webcam or smartphone cameras. The AI provides real-time feedback on exercise form, automatically counts repetitions, measures hold times, and flags technique errors. Physiotherapists review AI-generated performance data and provide personalized corrective guidance through scheduled video consultations. The platform delivers 8-week progressive exercise programs specifically designed for chronic non-specific low back pain, integrating objective movement monitoring with human therapeutic oversight to optimize adherence and clinical outcomes.

AI-Enhanced Telerehabilitation

Standard Telerehabilitation OTHER

This intervention delivers structured exercise therapy through pre-recorded video instructions without AI monitoring or automated feedback. Participants receive the same exercise components as the AI-enhanced group (flexibility, core stability, functional strength) but rely on video demonstrations and written instructions for proper technique. Physiotherapists conduct periodic consultations via video conferencing to monitor progress, provide guidance, and adjust exercise programs based on visual observation and participant self-reports. The 8-week progressive program represents current standard telerehabilitation practice for chronic non-specific low back pain, serving as an active comparator to isolate the specific effects of AI-enhanced movement analysis and real-time feedback systems.

Exercise-Only Telerehabilitation

Eligibility Criteria

• Age: 18 Years - 30 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Majmaah University: lead
• Galgotias University: collaborator

MeSH Terms

Conditions

Back Pain; Motor Activity

Condition Hierarchy (Ancestors)

Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Behavior

Central Study Contacts

Faizan Z PhD scholar, PhD

CONTACT

+919818899180; faizankashoo@gmial.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Masking Details: Outcome assessors evaluating primary endpoints (pain, disability, mobility, trunk endurance) are blinded to group allocation to prevent measurement bias. Independent research assistants conducting assessments remain unaware of participants' intervention assignments. Participants cannot be blinded due to intervention nature - they know whether receiving AI-enhanced telerehabilitation, standard telerehabilitation, or usual care. Physiotherapists delivering interventions cannot be blinded as they provide group-specific treatments. Data analysts remain blinded to group codes during statistical analysis until primary analyses complete. Principal investigator maintains randomization knowledge for safety monitoring but doesn't participate in outcome measurements.
• Purpose: TREATMENT
• Intervention Model: FACTORIAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD Scholar

Model Details: This three-arm parallel RCT uses single-blind design to evaluate AI-enhanced telerehabilitation for chronic low back pain in college students. Participants are randomized to: (1) AI-Enhanced Telerehabilitation with computer vision technology (MediaPipe Pose) providing real-time movement analysis and automated feedback via webcam, plus physiotherapist teleconsultations; (2) Standard Telerehabilitation with pre-recorded videos and periodic therapist sessions; or (3) Usual Care control. The AI system tracks exercise performance, counts repetitions, corrects posture, and enables personalized guidance. Primary outcomes include pain, disability, mobility, and trunk endurance over 6 weeks with 3-month follow-up. This addresses the research gap in AI-enhanced remote rehabilitation for young adults.

Study Record Dates

• First Submitted: August 21, 2025
• First Posted: August 28, 2025
• Study Start: October 1, 2025
• Primary Completion (Estimated): August 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: September 30, 2025

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE