Back to all available

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 protocol

neurology
orthopedics
rehabilitation

Abstract

Background: Chronic non-specific low back pain (CNSLBP) affects 40-52% of college students, representing a significant public health concern that impairs academic performance and quality of life. Traditional physiotherapy faces barriers including cost, accessibility, and time constraints. While telerehabilitation shows promise, current models lack objective exercise quality monitoring. Artificial intelligence (AI)-enhanced video analysis offers potential to bridge this gap by providing real-time movement assessment and personalized feedback. Objective: To determine the effectiveness of an AI-enhanced telerehabilitation program integrating automated video-based posture analysis with personalized feedback on pain reduction in college students with CNSLBP after six weeks, compared to exercise-only telerehabilitation and usual care. Methods: This single-blind, three-arm randomized controlled trial will recruit 120 college students aged 18-30 years with CNSLBP. Participants will be randomized to: (1) AI-enhanced telerehabilitation with automated video analysis and weekly therapist feedback, (2) exercise-only telerehabilitation without AI feedback, or (3) usual care control. The intervention duration is six weeks with assessments at baseline, Week 6, and three-month follow-up. Primary outcome is pain intensity (Numerical Rating Scale). Secondary outcomes include disability (Roland-Morris Disability Questionnaire), mobility (Timed Up and Go), trunk endurance (prone plank test), adherence rates, and platform usability. Expected Outcomes: The AI-enhanced group is hypothesized to demonstrate superior pain reduction, functional improvement, and exercise adherence compared to other groups. This research will provide evidence for integrating AI technology into telerehabilitation for young adults with CNSLBP. Keywords: chronic low back pain, telerehabilitation, artificial intelligence, college students, video analysis, physiotherapy
Ask to review this manuscript

Notes for potential reviewers

  • Volunteering is not a guarantee that you will be asked to review. There are many reasons: reviewers must be qualified, there should be no conflicts of interest, a minimum of two reviewers have already accepted an invitation, etc.
  • This is NOT OPEN peer review. The review is single-blind, and all recommendations are sent privately to the Academic Editor handling the manuscript. All reviews are published and reviewers can choose to sign their reviews.
  • What happens after volunteering? It may be a few days before you receive an invitation to review with further instructions. You will need to accept the invitation to then become an official referee for the manuscript. If you do not receive an invitation it is for one of many possible reasons as noted above.
  • PeerJ does not judge submissions based on subjective measures such as novelty, impact or degree of advance. Effectively, reviewers are asked to comment on whether or not the submission is scientifically and technically sound and therefore deserves to join the scientific literature. Our Peer Review criteria can be found on the "Editorial Criteria" page - reviewers are specifically asked to comment on 3 broad areas: "Basic Reporting", "Experimental Design" and "Validity of the Findings".
  • Reviewers are expected to comment in a timely, professional, and constructive manner.
  • Until the article is published, reviewers must regard all information relating to the submission as strictly confidential.
  • When submitting a review, reviewers are given the option to "sign" their review (i.e. to associate their name with their comments). Otherwise, all review comments remain anonymous.
  • All reviews of published articles are published. This includes manuscript files, peer review comments, author rebuttals and revised materials.
  • Each time a decision is made by the Academic Editor, each reviewer will receive a copy of the Decision Letter (which will include the comments of all reviewers).

If you have any questions about submitting your review, please email us at [email protected].