An intelligent data analysis-based medical management method for lower limb health of football athletes

Xiang Wang; Yongcheng Wang; Limin He; Xiang Wang; Yongcheng Wang; Limin He

doi:10.3934/mbe.2023624

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 8: 14005-14022. doi: 10.3934/mbe.2023624

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An intelligent data analysis-based medical management method for lower limb health of football athletes

1.
Department of Physical Education, Gansu University of Political Science and Law, Lanzhou 730030, China
2.
Volleyball Teaching and Research Department, Xi'an Physical Education University, Xi'an 710000, China
3.
Department of Physical Education, Lanzhou University, Lanzhou 730000, China

Academic Editor: Junxin Chen

Received: 02 February 2023 Revised: 29 May 2023 Accepted: 13 June 2023 Published: 21 June 2023

With increasingly mature commercial operations, football has become the most popular sport in the world. As the main body of football, athletes are prone to injury due to an increasing degree of competition intensity. Their health determines the length of these athletes careers, especially regarding the lower limbs that are mainly used. Therefore, the smart visualization approaches that can realize such function are in urgent demand in the area of sports healthcare. Benefitted by the strong ability of perception and analysis, a convolutional neural network (CNN) is utilized to construct an intelligent data analysis-based medical management method for the lower limb health of football athletes. First, the CNN is formulated as the main backbone, and its parameters are optimized for multiple rounds during the training stage. Then, a statistical analysis software named SPSS is introduced to assess the effect mechanism of different postures on lower limbs. Some experiments are carried out on simulative data to evaluate the proposed method, and results show a good performance of the proposed method.
- artificial intelligence,
- medical management,
- lower limb health,
- intelligent data analysis
Citation: Xiang Wang, Yongcheng Wang, Limin He. An intelligent data analysis-based medical management method for lower limb health of football athletes[J]. Mathematical Biosciences and Engineering, 2023, 20(8): 14005-14022. doi: 10.3934/mbe.2023624

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Abstract

With increasingly mature commercial operations, football has become the most popular sport in the world. As the main body of football, athletes are prone to injury due to an increasing degree of competition intensity. Their health determines the length of these athletes careers, especially regarding the lower limbs that are mainly used. Therefore, the smart visualization approaches that can realize such function are in urgent demand in the area of sports healthcare. Benefitted by the strong ability of perception and analysis, a convolutional neural network (CNN) is utilized to construct an intelligent data analysis-based medical management method for the lower limb health of football athletes. First, the CNN is formulated as the main backbone, and its parameters are optimized for multiple rounds during the training stage. Then, a statistical analysis software named SPSS is introduced to assess the effect mechanism of different postures on lower limbs. Some experiments are carried out on simulative data to evaluate the proposed method, and results show a good performance of the proposed method.

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