Research on real-time evaluation algorithm of human movement in tennis training robot

摘要

The system joined to outdoor supplies, and human body current sensors can give quantitative data about development or effect like a ball. However, these techniques? scope is uncertain in assessing sports skills at the individual level, similar to coaching, training, furthermore, replay examination measures. The reason for this article is to show another approach to perform programmed ID of tennis swings with ball impact error technology. The proposed Enhance Motor Learning Classification (EMLC) technique relies on movement slope vector stream and polynomial relapse, and RBF classifiers can recognize beforehand undetectable bogus swings. The proposed arrangement can catch two emotional swing procedure measurements from a small dataset for learning and coaching. Various training scenarios require flexible evaluation criteria, as evidenced by personalization and the assignment of different marking criteria to identify similar temporal and spatial patterns of tennis swings with players of varying skill levels. The proposed Enhance Motor Learning Classification (EMLC) is used to give better performance and results.