Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning
Swimmers must fully mobilize the muscles of the whole body during exercise, and it is necessary to study the protection of swimmers from muscle damage. Now, muscle damage is increasing year by year, and more athletes are affected. Therefore, studying the causes of muscle injuries and exploring more...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2022/2573058 |
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| author | Shimeng Huang Qiulan Luo Jingwen Liao |
| author_facet | Shimeng Huang Qiulan Luo Jingwen Liao |
| author_sort | Shimeng Huang |
| collection | DOAJ |
| description | Swimmers must fully mobilize the muscles of the whole body during exercise, and it is necessary to study the protection of swimmers from muscle damage. Now, muscle damage is increasing year by year, and more athletes are affected. Therefore, studying the causes of muscle injuries and exploring more effective treatments have become important research topics in the field of sports medicine. This study is mainly based on deep learning to analyze the protective effect of branched-chain amino acids on swimming athletes’ muscle injury. Due to the complex and changeable environment and the interference of unknown factors, a single sensor cannot meet the needs of obtaining information. Therefore, people have developed the technology of multisensor information fusion to obtain enough information. Multisensor data fusion technology can synthesize the information of each sensor and then obtain more comprehensive and accurate decision-making information. This study is mainly based on multisensor fusion and deep learning to analyze the impact of branched chain amino acids on Swimmers’ muscle health information. Finally, two experiments were designed in this article. The first experimental result showed that the pain level of the experimental group who took BCAA supplements was 19% lower than that of the control group that did not take the BCAA supplement within three days after exercise. The results of the second experiment show the following: after exercise, the creatine kinase activity value of the experimental group taking BCAA supplement was 4.38±1.45, and the creatine kinase activity value of the control group taking placebo was 5.42±2.12. It proves that BBCA can protect muscle damage by reducing the activity of creatine kinase. |
| format | Article |
| id | doaj-art-1647be7a820548eda07e471d85b3dd77 |
| institution | Kabale University |
| issn | 1754-2103 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-1647be7a820548eda07e471d85b3dd772025-08-20T03:54:32ZengWileyApplied Bionics and Biomechanics1754-21032022-01-01202210.1155/2022/2573058Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep LearningShimeng Huang0Qiulan Luo1Jingwen Liao2Swimming Teaching and Research OfficeDepartment of SportsScience Experiment CenterSwimmers must fully mobilize the muscles of the whole body during exercise, and it is necessary to study the protection of swimmers from muscle damage. Now, muscle damage is increasing year by year, and more athletes are affected. Therefore, studying the causes of muscle injuries and exploring more effective treatments have become important research topics in the field of sports medicine. This study is mainly based on deep learning to analyze the protective effect of branched-chain amino acids on swimming athletes’ muscle injury. Due to the complex and changeable environment and the interference of unknown factors, a single sensor cannot meet the needs of obtaining information. Therefore, people have developed the technology of multisensor information fusion to obtain enough information. Multisensor data fusion technology can synthesize the information of each sensor and then obtain more comprehensive and accurate decision-making information. This study is mainly based on multisensor fusion and deep learning to analyze the impact of branched chain amino acids on Swimmers’ muscle health information. Finally, two experiments were designed in this article. The first experimental result showed that the pain level of the experimental group who took BCAA supplements was 19% lower than that of the control group that did not take the BCAA supplement within three days after exercise. The results of the second experiment show the following: after exercise, the creatine kinase activity value of the experimental group taking BCAA supplement was 4.38±1.45, and the creatine kinase activity value of the control group taking placebo was 5.42±2.12. It proves that BBCA can protect muscle damage by reducing the activity of creatine kinase.http://dx.doi.org/10.1155/2022/2573058 |
| spellingShingle | Shimeng Huang Qiulan Luo Jingwen Liao Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning Applied Bionics and Biomechanics |
| title | Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning |
| title_full | Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning |
| title_fullStr | Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning |
| title_full_unstemmed | Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning |
| title_short | Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning |
| title_sort | analysis of the effect of branched chain amino acids on muscle health information of swimmers based on multisensor fusion and deep learning |
| url | http://dx.doi.org/10.1155/2022/2573058 |
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