Telemedicine-Based Rehabilitation: Evidence, Applications and Innovative Technologies
Abstract
Objective: This narrative review synthesizes current evidence on telehealth-based physiotherapy and telerehabilitation, focusing on clinical effectiveness, commonly used technologies, and key methodological and equity-related barriers affecting implementation.
Material and methods: The review followed international evidence-synthesis standards. Comprehensive searches were conducted in PubMed/MEDLINE, Scopus, Web of Science, PEDro, and CINAHL for studies published between 2020–2025 using MeSH terms and keywords related to telehealth and digital physiotherapy. Eligible studies included systematic reviews, randomized trials, observational research, methodological evaluations, and qualitative studies. Non-rehabilitation and low-quality studies were excluded. Owing to heterogeneity, findings were integrated thematically.
Findings: Across musculoskeletal, neurological, cardiopulmonary, pediatric, and geriatric populations, telerehabilitation demonstrates safety and clinical effectiveness comparable to in-person physiotherapy, especially for exercise and education-based interventions. Remote functional assessments using video, wearables, and AI tools show strong validity. However, inconsistent protocols, small samples, and limited follow-up restrict generalizability. Digital inequities, technological barriers, and challenges among older or low-literacy users persist. Hybrid models enhance outcomes for complex cases, while structured progression, clinician feedback, and user-friendly platforms are critical for success.
Conclusion: Telehealth and telerehabilitation represent increasingly important components of modern physiotherapy, offering accessible and, under appropriate conditions, effective care. Current evidence indicates outcomes comparable to traditional rehabilitation for selected populations and intervention types, particularly structured, exercise-based programs delivered with adequate technological infrastructure and clinical supervision, although methodological heterogeneity, limited long-term data, and digital access gaps constrain broader generalization. Emerging AI, VR/AR tools, and hybrid models hold promise for advancing telehealth-supported physiotherapy, pending further controlled, long-term research.
Keywords
References
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Details
Primary Language
English
Subjects
Digital Health
Journal Section
Review
Authors
Publication Date
June 30, 2026
Submission Date
December 22, 2025
Acceptance Date
June 24, 2026
Published in Issue
Year 2026 Volume: 10 Number: 1