AI analysis system facilitates athlete evaluation


Special: 2022 Winter Olympics

(Photo/Fudan University)

A team from Fudan University has developed an artificial intelligence-based training analysis system to aid in the performance evaluation of winter sports athletes participating in the Beijing 2022 Winter Olympics , which will begin on February 4.

Zhang Lihua, team leader and professor of engineering and technology at Shanghai University, said the system analyzes athletes’ movements, postures, speed and other performance indicators during training through to algorithms, contributing to the creation of personalized training plans for each athlete and the overall effectiveness of scientific training.

He launched the idea of ​​setting up the system in 2019, when the General Sports Administration sought to promote the winter sports equipment industry for the Games.

His idea was also backed by Kristin Collins, a sports performance consultant at the administration’s Winter Sports Management Center in Beijing.

“It was two years of collaborative work with the sports administration of Jilin Province, a northeast region that is often snow-covered in winter and good for sports training,” Zhang said.

Normally, coaches observe athletes in training to provide feedback on their performance, but the analytics system allows real-time digital monitoring of athletes through high-definition cameras, which identify every movement they make and summarize their performance, Zhang said.

“It relieves coaches of this burden and improves training effectiveness through quantitative scientific analysis,” he said.

For sports like figure skating, the system is also able to improve the standardization and aesthetics of athletes’ performance postures, thanks to its 3D sensing and pose estimation functions, he added.

Other sports, such as soccer, can also use the system for real-time monitoring and analysis, Zhang said.

“A friend’s kids in the US love ice hockey and want to use the system at home to improve their performance,” he said. “The system could eventually be used not only to serve national sports competitions, but also for the general public.”

Zhang said the team studied the system’s functions for sports competitions open to novice and amateur athletes, for the creation of AI assistant judges, and for the development of smart sports venues and facilities.


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