Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo
IntroductionThe aim of this study is to compare the injury patterns of female water polo players before and after the implementation of the Male-Assisted Female Training (MAFT) program. The study seeks to identify key factors influencing these changes and propose corresponding injury prevention meas...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Digital Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2024.1503831/full |
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| author | Xuehui Feng Xuehui Feng Zhibin Wang Zhibin Wang Zheng Wang Zheng Wang Chen He Chen He Hongxing Xun Yuanfa Chen Jie Ding Jie Ding Gen Chen Gen Chen Zhe Liu Zhe Liu |
| author_facet | Xuehui Feng Xuehui Feng Zhibin Wang Zhibin Wang Zheng Wang Zheng Wang Chen He Chen He Hongxing Xun Yuanfa Chen Jie Ding Jie Ding Gen Chen Gen Chen Zhe Liu Zhe Liu |
| author_sort | Xuehui Feng |
| collection | DOAJ |
| description | IntroductionThe aim of this study is to compare the injury patterns of female water polo players before and after the implementation of the Male-Assisted Female Training (MAFT) program. The study seeks to identify key factors influencing these changes and propose corresponding injury prevention measures.MethodsWe utilized pattern analysis and classification techniques to explore the injury data. A Hypergraph Neural Network (HGNN) was employed for pattern extraction, where each athlete was represented as a node in a hypergraph, with node dimensions capturing high-order relational embedding information. We applied the graph Laplacian operator to aggregate neighborhood features and visualize structural and feature differences in hypergraphs based on different influencing factors. Additionally, we introduced graph structure regularization to improve classification accuracy and prevent overfitting in the relatively small dataset, enhancing our ability to identify critical factors affecting injury types.ResultsThe analysis revealed significant differences in injury patterns before and after the MAFT program, with specific influencing factors being identified through both pattern recognition and classification techniques. The classification models, supported by graph structure regularization, achieved improved accuracy in distinguishing key features that contributed to changes in injury types.DiscussionThese findings provide insights into the critical factors influencing injury patterns in female water polo players and highlight the effectiveness of the MAFT program in mitigating certain injury risks. Based on the identified features, we propose targeted preventive measures to reduce injury incidence, particularly in relation to changes brought about by the MAFT training mode. Further research is needed to refine these measures and explore their long-term effectiveness. |
| format | Article |
| id | doaj-art-0220aae5720a467fb1756905cc8a2447 |
| institution | Kabale University |
| issn | 2673-253X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj-art-0220aae5720a467fb1756905cc8a24472025-01-06T06:59:41ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2025-01-01610.3389/fdgth.2024.15038311503831Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water poloXuehui Feng0Xuehui Feng1Zhibin Wang2Zhibin Wang3Zheng Wang4Zheng Wang5Chen He6Chen He7Hongxing Xun8Yuanfa Chen9Jie Ding10Jie Ding11Gen Chen12Gen Chen13Zhe Liu14Zhe Liu15Key Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaHunan Institute of Sports Science, Hunan, ChinaGuangxi Sports Trauma Center, Guangxi, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaKey Laboratory of Sports Trauma and Rehabilitation of General Administration of Sport of the People's Republic of China, Beijing, ChinaNational Research Institute of Sports Medicine (NRISM), Beijing, ChinaIntroductionThe aim of this study is to compare the injury patterns of female water polo players before and after the implementation of the Male-Assisted Female Training (MAFT) program. The study seeks to identify key factors influencing these changes and propose corresponding injury prevention measures.MethodsWe utilized pattern analysis and classification techniques to explore the injury data. A Hypergraph Neural Network (HGNN) was employed for pattern extraction, where each athlete was represented as a node in a hypergraph, with node dimensions capturing high-order relational embedding information. We applied the graph Laplacian operator to aggregate neighborhood features and visualize structural and feature differences in hypergraphs based on different influencing factors. Additionally, we introduced graph structure regularization to improve classification accuracy and prevent overfitting in the relatively small dataset, enhancing our ability to identify critical factors affecting injury types.ResultsThe analysis revealed significant differences in injury patterns before and after the MAFT program, with specific influencing factors being identified through both pattern recognition and classification techniques. The classification models, supported by graph structure regularization, achieved improved accuracy in distinguishing key features that contributed to changes in injury types.DiscussionThese findings provide insights into the critical factors influencing injury patterns in female water polo players and highlight the effectiveness of the MAFT program in mitigating certain injury risks. Based on the identified features, we propose targeted preventive measures to reduce injury incidence, particularly in relation to changes brought about by the MAFT training mode. Further research is needed to refine these measures and explore their long-term effectiveness.https://www.frontiersin.org/articles/10.3389/fdgth.2024.1503831/fullhypergraphhigh-order connectioninjury patternswomen’s water poloMale-Assisting-Female-Training |
| spellingShingle | Xuehui Feng Xuehui Feng Zhibin Wang Zhibin Wang Zheng Wang Zheng Wang Chen He Chen He Hongxing Xun Yuanfa Chen Jie Ding Jie Ding Gen Chen Gen Chen Zhe Liu Zhe Liu Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo Frontiers in Digital Health hypergraph high-order connection injury patterns women’s water polo Male-Assisting-Female-Training |
| title | Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo |
| title_full | Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo |
| title_fullStr | Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo |
| title_full_unstemmed | Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo |
| title_short | Male-assisted training and injury patterns: hypergraph-enhanced analysis of injuries in women’s water polo |
| title_sort | male assisted training and injury patterns hypergraph enhanced analysis of injuries in women s water polo |
| topic | hypergraph high-order connection injury patterns women’s water polo Male-Assisting-Female-Training |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2024.1503831/full |
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