Sistema de inteligencia artificial para la asistencia y corrección de técnicas de deportistas de alto rendimiento por visión artificial
DOI:
https://doi.org/10.5281/zenodo.17527815Keywords:
High-performance sport, Artificial Intelligence, Media Pipe Pose, Python, Computer visionAbstract
Currently, computer vision (CV) is experiencing significant growth due to advances in artificial intelligence (AI), machine learning, the increasing availability of data and computing power. The main areas of development of IA are the manufacturing industry, healthcare, automotive, security and surveillance, agriculture, sports, and many others. Regarding high-performance sports, it is established that the major problem is the ratio between the number of trained coaches and the number of athletes they attend to, understanding that the attention time for each athlete is diminished when the number of people being trained increases, resulting in a delay in their athletic progress and possible injuries due to the development of erroneous techniques due to such inattention. This work develops an assistance system for high-performance athletes based on artificial intelligence, for the enhancing of techniques and correction of execution errors. It is based on computer vision algorithms that allow establishing training techniques and execution mechanics of some exercises, using real-time video in which athletes are informed of the correct or deficient execution of their technique. Results and conclusions describe the details of the development applied to techniques of athletes in skating and the scope of the prototype implementation.
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Copyright (c) 2025 Carlos Alfonso Trejo Villanueva, Derlis Hernández Lara, Emmanuel Tonatihu Juárez Velázquez, Cinthia Estela Trejo Villanueva
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