Abstract
Athletes voluntarily change their sportive behavior in order to improve performance or to reduce load. If this process is guided by feedback loops, characteristics of adaptive systems are met. The occurring adaptive change is relevant to achieving a goal or objective. In a similar manner, smart sports equipment may alter its properties depending on environmental conditions. In order to automatically give feedback on how to continue exercising and/or to adjust the sports equipment during the physical activity, intelligent devices are required. These devices rely on models for recognition and classification of patterns in the motion or activity currently performed. Different methods and models, such as Neural Networks, Hidden Markov models or Support Vector Machines have proven to be applicable for this purpose. Examples from recreational running, mountain-biking, exercising on weight training machines and long distance running illustrate the principle.
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Baca, A. (2014). Adaptive Systems in Sports. In: Pardalos, P., Zamaraev, V. (eds) Social Networks and the Economics of Sports. Springer, Cham. https://doi.org/10.1007/978-3-319-08440-4_7
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DOI: https://doi.org/10.1007/978-3-319-08440-4_7
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