A Systematic Literature Review of Intelligent Data Analysis Methods for Smart Sport Training

被引:78
作者
Rajsp, Alen [1 ]
Fister, Iztok, Jr. [1 ]
机构
[1] Univ Maribor, Fac Elect Engn & Comp Sci, SI-2000 Maribor, Slovenia
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 09期
关键词
intelligent data analysis; sport training; smart sport training; data mining; computational intelligence; deep learning; machine learning; ARTIFICIAL-INTELLIGENCE; MACHINE; SENSOR; FITNESS; CLASSIFICATION; PERFORMANCE; EXTRACTION; ALGORITHM; NETWORKS; DEVICES;
D O I
10.3390/app10093013
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The rapid transformation of our communities and our way of life due to modern technologies has impacted sports as well. Artificial intelligence, computational intelligence, data mining, the Internet of Things (IoT), and machine learning have had a profound effect on the way we do things. These technologies have brought changes to the way we watch, play, compete, and also train sports. What was once simply training is now a combination of smart IoT sensors, cameras, algorithms, and systems just to achieve a new peak: The optimum one. This paper provides a systematic literature review of smart sport training, presenting 109 identified studies. Intelligent data analysis methods are presented, which are currently used in the field of Smart Sport Training (SST). Sport domains in which SST is already used are presented, and phases of training are identified, together with the maturity of SST methods. Finally, future directions of research are proposed in the emerging field of SST.
引用
收藏
页数:31
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