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

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...

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Main Author: Liu Xiaodi
Format: Article
Language:English
Published: Sciendo 2023-07-01
Series:Applied Mathematics and Nonlinear Sciences
Subjects:
Online Access:https://doi.org/10.2478/amns.2021.2.00189
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author Liu Xiaodi
author_facet Liu Xiaodi
author_sort Liu Xiaodi
collection DOAJ
description 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.
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spelling doaj.art-cbe5ef669a8d44638df5f1062abf94702024-03-11T10:05:44ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562023-07-018252953810.2478/amns.2021.2.00189Design and evaluation of intelligent teaching system on basic movements in PELiu Xiaodi01College of Physical Education, Xi’an Physical Education University, Xi’an, Shaanxi710068, ChinaFor 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.https://doi.org/10.2478/amns.2021.2.00189pehuman pose estimationteaching system
spellingShingle Liu Xiaodi
Design and evaluation of intelligent teaching system on basic movements in PE
Applied Mathematics and Nonlinear Sciences
pe
human pose estimation
teaching system
title Design and evaluation of intelligent teaching system on basic movements in PE
title_full Design and evaluation of intelligent teaching system on basic movements in PE
title_fullStr Design and evaluation of intelligent teaching system on basic movements in PE
title_full_unstemmed Design and evaluation of intelligent teaching system on basic movements in PE
title_short Design and evaluation of intelligent teaching system on basic movements in PE
title_sort design and evaluation of intelligent teaching system on basic movements in pe
topic pe
human pose estimation
teaching system
url https://doi.org/10.2478/amns.2021.2.00189
work_keys_str_mv AT liuxiaodi designandevaluationofintelligentteachingsystemonbasicmovementsinpe