The role of technology for accelerated motor learning in sport

  • Matevž Pustišek
  • Yu WeiEmail author
  • Yunchuan Sun
  • Anton Umek
  • Anton Kos
Original Article


Wearable devices measuring some physical or physiological quantity of an individual have already become a part of daily life for many people. While such simple devices output mainly the statistical values of measured quantities or count events, demands in sport are more stringent. Quantities of interest must be measured in a wider range, with a greater precision, and with a higher sampling frequency. We present a short introduction to motor learning in sport and its needs for technology back-up. We present properties and limitations of various sensors used for sport activity signal acquisition, means of communication, and properties and limitations of communication channels. We shed some light on the analysis of various aspects of sport activity signal and data processing. We present timing, spatial, and computational power constraints of processing. Attention is given also to the state of the art data processing techniques such as machine learning and data mining. We also put into context some technological trends and challenges in sport, such as the Internet of Things, fog and cloud computing, smart sport equipment, and real-time biofeedback systems and applications.


Motor learning Sensors Sport activity signal acquisition Biofeedback system Sport data analysis Machine learning in sport Smart sport equipment 



The authors acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0246).


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Matevž Pustišek
    • 1
  • Yu Wei
    • 2
    Email author
  • Yunchuan Sun
    • 3
  • Anton Umek
    • 1
  • Anton Kos
    • 1
  1. 1.Faculty of Electrical EngineeringUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Computer Teaching and Research SectionCapital University of Physical Education and SportsBeijingChina
  3. 3.Business schoolBeijing Normal UniversityBeijingChina

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