Abstract
The analysis of the mechanical characteristics of the knee flexion movement can effectively improve the athlete’s competitiveness and provide an important theoretical basis for the study of human mechanics. The human knee is an important analysis goal. In the force analysis of the flexion movement of the athlete, the flexion movement characteristics of the knee joint of the athlete are mainly analyzed. The traditional biological method only analyzes the force of all the human joints in the athlete, but ignored the athlete’s knee test. In this paper, we propose a method to analyze the mechanical characteristics of knee flexion movement in the human body. Taking the throwing movement as an example, the professional far-infrared system is used to test the whole process of the flexion movement of the athletes and the mechanics model of multi-rigid body is established to carry out the mechanical characteristics analysis of the knee flexion movement, and analyze the knee force situation of the athletes under different movements in detail. In order to verify the effectiveness of the proposed method, the experiment is carried out. From the experimental results, it can be seen that the method for researching the mechanical characteristics of the knee flexion movement can be used to effectively analyze the knee force.
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Li, H. (2021). Construction of Human Knee Joint Mechanics Model and Study on Mechanical Characteristics of Flexion Movement Based on Neural Network Algorithm. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1282. Springer, Cham. https://doi.org/10.1007/978-3-030-62743-0_7
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DOI: https://doi.org/10.1007/978-3-030-62743-0_7
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