| AI-Powered Telerehabilitation in Musculoskeletal Care: A Narrative Review of Access and Efficacy |
| Paper ID : 1009-ISCSR3 (R1) |
| Authors |
|
ibrahim mohamed mohamed * physical therapy at Cairo university |
| Abstract |
| Background: Telerehabilitation has emerged as a transformative approach in physical therapy access shortage particularly when combined with artificial intelligence (AI) for musculoskeletal (MSK) disorders. It has shown numerous benefits, including improving access, promoting patient adherence, and reducing costs. Objectives: To evaluate the engagement and clinical outcomes of remote digital care program in patients with MSK conditions, with a particular focus on low- and middle-income countries (LMICs) and populations with limited time for in-person care. Methods: A narrative review was conducted to synthesize evidence from studies published between 2018 and 2025, sourced from PubMed, Scopus, and Google Scholar to evaluate the application of AI in telerehabilitation. The review evaluates the application of AI in telerehabilitation, Inclusion criteria: RCTs evaluating AI-driven telerehabilitation (wearable sensors, computer vision, machine learning, and smartphones) for musculoskeletal disorders, reporting pain/functional outcomes. Excluded: non-RCTs, non-English studies. Platforms assessed included SWORD Health (n=5 RCTs), Kaia Health (n=3 RCTs), and others (n=9 RCTs). Results: platforms like SWORD Health and Kaia Health achieved response rates ranging from 56.6 to 63.6% pain reduction in chronic MSK pain. in assessing a digital care program versus conventional physiotherapy for Chronic Shoulder Pain and chronic low back pain there is no significant differences between groups are found in improvements of function and pain. Economically, AI solutions reduce healthcare costs by 30–60%, particularly in LMICs, while improving access for population who can hardly afford in-person physical therapy sessions. Conclusion: AI in telerehabilitation is achieving a clinically significant results in function and pain and is cost effective but still challenges persist, including data privacy vulnerabilities in platforms, difficult in user experience for elderly population. Technical limitations, such as sensor inaccuracies in elderly and obese patients, also exist. For Future directions, hybrid care models blending AI with physiotherapists so it can reduce hospital readmissions and number of sessions. |
| Keywords |
| AI-Powered Telerehabilitation; Musculoskeletal Disorders; Remote Monitoring; Wearable Sensors. |
| Status: Abstract Accepted |