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

被引:77
|
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
相关论文
共 50 条
  • [21] Training Methods in the Sport of Surfing: A Scoping Review
    Donaldson, Terry
    Scantlebury, Malcolm
    Furness, James
    Kemp-Smith, Kevin
    Newcomer, Sean
    Climstein, Mike
    STRENGTH AND CONDITIONING JOURNAL, 2022, 44 (03) : 21 - 32
  • [22] Exercise training and atrial fibrillation: a systematic review and literature analysis
    Leggio, M.
    Fusco, A.
    Coraci, D.
    Villano, A.
    Filardo, G.
    Mazza, A.
    Loreti, C.
    Serafini, E.
    Biscotti, L.
    Bernabei, R.
    Padua, L.
    Giovannini, S.
    EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES, 2021, 25 (16) : 5163 - 5175
  • [23] Breast cancer intelligent analysis of histopathological data: A systematic review
    Zeiser, Felipe Andre
    da Costa, Cristiano Andre
    Roehe, Adriana Vial
    Righi, Rodrigo da Rosa
    Marques, Nuno Miguel Cavalheiro
    APPLIED SOFT COMPUTING, 2021, 113
  • [24] Big data stream analysis: a systematic literature review
    Taiwo Kolajo
    Olawande Daramola
    Ayodele Adebiyi
    Journal of Big Data, 6
  • [25] Bibliometric Analysis and Systematic Literature Review on Data Visualization
    Kim, Byeongmok
    Kim, Yonggab
    Duffy, Vincent G.
    DIGITAL HUMAN MODELING AND APPLICATIONS IN HEALTH, SAFETY, ERGONOMICS AND RISK MANAGEMENT, DHM 2023, PT II, 2023, 14029 : 490 - 502
  • [26] Big data stream analysis: a systematic literature review
    Kolajo, Taiwo
    Daramola, Olawande
    Adebiyi, Ayodele
    JOURNAL OF BIG DATA, 2019, 6 (01)
  • [27] Approaches for data collection and process standardization in smart manufacturing: Systematic literature review
    Schlemitz, Alexandra
    Mezhuyev, Vitaliy
    JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2024, 38
  • [28] A Systematic Literature Review of Deep Learning Approaches in Smart Meter Data Analytics
    Breitenbach, Johannes
    Gross, Jan
    Wengert, Manuel
    Anurathan, James
    Bitsch, Rico
    Kosar, Zafer
    Tuelue, Emre
    Buettner, Ricardo
    2022 IEEE 46TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2022), 2022, : 1337 - 1342
  • [29] Approaches for data collection and process standardization in smart manufacturing: Systematic literature review
    Schlemitz, Alexandra
    Mezhuyev, Vitaliy
    Journal of Industrial Information Integration, 2024, 38
  • [30] Dam monitoring data analysis methods: A literature review
    Li, Bin
    Yang, Jie
    Hu, Dexiu
    STRUCTURAL CONTROL & HEALTH MONITORING, 2020, 27 (03):