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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 wider range, with greater precision, and with 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. In conclusion we present some technological trends and challenges in sport, such as Internet of Things, smart sport equipment, and real-time biofeedback systems and applications.
Kos et al. (Mon,) studied this question.