Designing an Interactive Tool for Physiotherapy to Support Diagnosing Musculoskeletal Disorders in Musicians Using Clinical Movement Analysis

Musculoskeletal disorders (MSDs) are prevalent among musicians, posing challenges for both musicians and physiotherapists. Clinical Movement Analysis (CMA) permits the accurate and objective assessment of posture and movement during musical performance, which can enhance MSD diagnosis. However, tools for CMA data analysis that are tailored to physiotherapy workflows are lacking. The aim of this study was to design an interactive tool that integrates CMA data to assist physiotherapists in diagnosing musician-specific MSDs, addressing limitations of traditional diagnostic methods. Following a user-centered design process and visualization design model, the tool was iteratively refined with expert feedback. It meets six key requirements by integrating biomechanical data (i.e., joint rotation angles and muscle activity) with clinical findings to support hypothesis-driven assessments. The prototype features an intuitive, mobile-friendly interface, interactive visualizations of time-oriented data, and reference values for detecting abnormalities. It enables efficient analysis of posture and movement patterns while linking findings to diagnostic hypotheses. Preliminary evaluations have highlighted its usability, alignment with physiotherapy workflows, and potential to bridge the gap between CMA data and clinical decision-making. By enhancing MSD diagnosis and treatment planning, the tool promises to improve patient outcomes. Future work involves clinical validation, broader application to diverse musician populations, and the incorporation of advanced analytics, including machine learning, to further enhance the tool's capabilities.