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Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes
Physical training has a high degree of participation all over the world. With the opening of the era of national fitness, physical training has become more popular from the original specialization, and the complex training methods and contents have gradually become simplified. The development and ch...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439893/ https://www.ncbi.nlm.nih.gov/pubmed/36101807 http://dx.doi.org/10.1155/2022/7323146 |
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author | Li, Kai Zhang, Jinqian Qu, Qingling Li, Bairan Kim, Sukwon |
author_facet | Li, Kai Zhang, Jinqian Qu, Qingling Li, Bairan Kim, Sukwon |
author_sort | Li, Kai |
collection | PubMed |
description | Physical training has a high degree of participation all over the world. With the opening of the era of national fitness, physical training has become more popular from the original specialization, and the complex training methods and contents have gradually become simplified. The development and change of physical training has also brought many problems to the professional training of athletes, such as high training intensity but poor effect, insufficient training posture, and long-term physical injury. In order to help athletes achieve better results in physical training and reduce the probability of injury, taking sprint training as an example, this article adopted the sports and body data of elite athletes through intelligent technology and big data analysis, established a human motion model from the perspective of biomechanics, and then conducted a corresponding test run experiment for athletes. The experimental results suggested that drag resistance running could improve the specific strength quality of sprinting. At the same time, when using resistance load for training, the maximum speed should not exceed 90% of the maximum speed without resistance. The average horizontal maximum velocity decreased by approximately 9% when training under a resistance load, and the best training results were obtained by training athletes within this range. |
format | Online Article Text |
id | pubmed-9439893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94398932022-09-12 Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes Li, Kai Zhang, Jinqian Qu, Qingling Li, Bairan Kim, Sukwon Contrast Media Mol Imaging Research Article Physical training has a high degree of participation all over the world. With the opening of the era of national fitness, physical training has become more popular from the original specialization, and the complex training methods and contents have gradually become simplified. The development and change of physical training has also brought many problems to the professional training of athletes, such as high training intensity but poor effect, insufficient training posture, and long-term physical injury. In order to help athletes achieve better results in physical training and reduce the probability of injury, taking sprint training as an example, this article adopted the sports and body data of elite athletes through intelligent technology and big data analysis, established a human motion model from the perspective of biomechanics, and then conducted a corresponding test run experiment for athletes. The experimental results suggested that drag resistance running could improve the specific strength quality of sprinting. At the same time, when using resistance load for training, the maximum speed should not exceed 90% of the maximum speed without resistance. The average horizontal maximum velocity decreased by approximately 9% when training under a resistance load, and the best training results were obtained by training athletes within this range. Hindawi 2022-08-26 /pmc/articles/PMC9439893/ /pubmed/36101807 http://dx.doi.org/10.1155/2022/7323146 Text en Copyright © 2022 Kai Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Kai Zhang, Jinqian Qu, Qingling Li, Bairan Kim, Sukwon Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title | Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title_full | Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title_fullStr | Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title_full_unstemmed | Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title_short | Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes |
title_sort | application of biomechanics based on intelligent technology and big data in physical fitness training of athletes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439893/ https://www.ncbi.nlm.nih.gov/pubmed/36101807 http://dx.doi.org/10.1155/2022/7323146 |
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