Design and evaluation of intelligent teaching system on basic movements in PE

Abstract

Abstract For a long time, the situation of students’ learning in physical education (PE) was not optimistic, especially the basic movement learning after class, which lacked effective online learning tools. With the in-depth research of deep neural network and the rapid development of computer hardware, the artificial intelligence technology based on deep learning has performed well in the field of basic teaching. Therefore, in this paper, an intelligent teaching system of basic movements in PE is designed. First, the information of coordinate points is collected according to the Gaussian model, and the pose of students is estimated by OpenPose. Second, the overall architecture and functional modules of the system are designed. Finally, the deviation limbs that affect the standard of overall movements are identified by the matching algorithm, which realises the evaluation and feedback of basic movements in PE. Through this teaching system, teachers can obtain the learning situation of students’ movements, and students can adjust their movements through the feedback, which achieves the convenient interaction of PE teaching.