Assessing Sports Performances Using an Artificial Intelligence-Driven System
Giuseppe Annino, Vincenzo Bonaiuto, Francesca Campoli, Lucio Caprioli, Saeid Edriss, Elvira Padua, Emilio Panichi, Cristian Romagnoli, Naomi Romagnoli, Andrea Zanela
Abstract
Accurate observation of specific athletes' movements can assist coaches in assessing sporting gestures and addressing specific technical flaws, thereby enhancing overall performance. In addition, the system could support the biomechanical study in case of those technical personalisms that could lead to excessive overloading of the muscle-tendon and joint apparatus, resulting in an increased risk of injury. In this paper we propose the use of a recently developed system that employs artificial intelligence techniques to provide a reliable estimation of human body pose, opening up new possibilities for sports-related applications.