Evaluation and Refinement of Elbow Recovery in Sports Medicine Using Smart Tracking Technologies - Sergio Alonso-Rollán; Sergio Márquez-Sánchez; Albano Carrera; Isaac M. S. Froes; Juan F. Blanco (Advances in Distributed Computing and Artificial Intelligence Journal)
Elbow injuries, prevalent in various sports, significantly impact an athlete’s performance and career longevity. Traditional rehabilitation methods, while effective to a degree, often miss the mark in terms of precision and personalised care. This gap necessitates a shift towards more sophisticated rehabilitation strategies. This study introduces a pioneering approach in elbow rehabilitation, utilising cutting-edge wearable tracking technologies along with the telerehabilitation paradigm. The focus is on increasing the precision and efficacy of rehabilitation processes. We developed a state-of-the-art wearable device, equipped with sophisticated sensors, to accurately track elbow joint movements, including position, rotation, and flexion, in real-time. The device provides detailed data, allowing for nuanced diagnosis and effective monitoring during rehabilitation phases. This data is integrated into a specialised application, enabling comprehensive data analysis and the formulation of personalised rehabilitation plans with real-time feedback. The device demonstrated a notable improvement in the precision of monitoring and effectiveness of rehabilitation strategies, allowing the measurement of the range of motion (RoM) within an error of ±3 degrees. A comparative analysis with traditional methods revealed significant advancements in accuracy, adherence to prescribed rehabilitation regimens, and overall speed of recovery.