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3D Visualization Analysis of Motion Trajectory of Knee Joint in Sports Training Based on Digital Twin.

Authors :
Chen, Jian
Source :
Computational Intelligence & Neuroscience. 6/6/2022, p1-9. 9p.
Publication Year :
2022

Abstract

With the development of China's social economy, the pace of people's life is also accelerating. Therefore, in the face of the increasing pressure of life and work, people have begun to pay more and more attention to improving their physical fitness and they also pay more and more attention to sports in their spare time. The knee joint is a very important body part that will be involved in sports. Therefore, in sports, it is very important for healthy sports to pay attention to the state of the knee joint at all times and avoid injury to the knee joint during sports. The three-dimensional visual analysis of the knee joint movement trajectory in sports training refers to the trajectory capture and three-dimensional visual analysis of the knee joint movement in sports training based on the computer-based description and understanding of model technology. The three-dimensional visual analysis of the motion trajectory of the knee joint in sports training is conducive to the attention and analysis of the motion state of the knee joint in sports training, so as to help find problems and avoid knee joint damage during sports training as much as possible. This paper aims to study the 3D visualization analysis of knee joint motion trajectory in sports training based on digital twin and establish a 3D visualization system of knee joint motion trajectory based on digital twin technology, and based on this system, the three-dimensional visualization experiment of knee joint movement trajectory in sports training is carried out. The experiment concluded that the signal-to-noise ratio of the three-dimensional visualization image of the knee joint movement trajectory in sports training based on the three-dimensional visualization system established by the digital twin is 68% and the clarity is 89%. It shows that the system has a good 3D visualization effect. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
157287293
Full Text :
https://doi.org/10.1155/2022/3988166