Analysis of tennis technical movement training strategy in colleges and universities under the background of big data technology

Abstract

This paper first explains the tennis technical action representation and matching technology, using the Euler angle method to represent the coordinates of the tennis action gesture, realizing the deconstruction of the action gesture through the gesture-solving algorithm, and then using the weighted Euclidean distance to match the tennis gesture to the action. Secondly, we constructed the tennis technical movement training strategy for colleges and universities based on the task-driven teaching method, and gave the teaching experiment method to analyze the effectiveness of the strategy. Finally, the data was analyzed by examining the muscle characteristics of tennis technical movements and the teaching effect of task-driven teaching. The results showed that the maximal EMG integral value of the muscles was 32.91uV.s in the level 1 group and 87.91uV.s in the level 2 group, and the maximal angular velocity of the ankle-knee-hip joints was 645.23±189.42°/s and the minimum angular velocity of the hip joints was 461.87±115.08°/s in all the landing modes. 115.08°/s. The task-driven teaching method can effectively improve the students’ tennis learning and technical level and enhance the quality of tennis technical teaching in colleges and universities.