Personalized Physiotherapy Using Artificial Intelligence in Rare Musculoskeletal Disorders: Literature Review

Abstract: The advent of artificial intelligence (AI) in the realm of personalized physiotherapy marks a pivotal shift, especially concerning the management of rare musculoskeletal disorders. Conventional physiotherapeutic strategies frequently fall short in addressing the intricate and individualized requirements of patients with uncommon clinical presentations, thereby underscoring the necessity for advanced, adaptable methodologies. Leveraging AI-driven data analytics and machine learning algorithms, clinicians can now devise highly individualized rehabilitation protocols that account for each patient's unique clinical and genetic characteristics, thus refining both diagnostic accuracy and therapeutic effectiveness. Recent literature underscores the capacity of AI-enhanced interventions, including interactive digital platforms and tailored exergaming, to bolster patient participation and adherence by targeting specific functional impairments and fostering greater motivation. Additionally, AI's integration within precision medicine frameworks accelerates the identification and optimization of therapeutic pathways, further expediting the development of patient-specific treatments. The purpose of this review is to synthesize current evidence regarding the implementation of AI in personalized physiotherapy for rare musculoskeletal disorders, evaluating its impact on clinical outcomes and outlining future directions for research and practice. Collectively, these advancements signify a transformative era in individualized care, with AI poised to reshape both therapeutic paradigms and the broader landscape of rare disease management. Keywords: artificial intelligence, personalized physiotherapy, rare musculoskeletal disorders, machine learning, precision medicine. Title: Personalized Physiotherapy Using Artificial Intelligence in Rare Musculoskeletal Disorders: Literature Review Author: Zourna Victoria, Merteki Chrysoula, Drosos Filippos -Stylianos, Papaggelis Dimitris, Stefani Sevasti, Vaitsis Nikolaos, Aggelakou-Vaitsi Stamatina International Journal of Novel Research in Healthcare and Nursing ISSN 2394-7330 Vol. 13, Issue 1, January 2026 - April 2026 Page No: 133-141 Novelty Journals Website: www.noveltyjournals.com Published Date: 17-April-2026 DOI: https://doi.org/10.5281/zenodo.19627273 Paper Download Link (Source) https://www.noveltyjournals.com/upload/paper/Personalized%20Physiotherapy%20Using%20Artificial-17042026-3.pdf