engleski

Machine Learning for Individualized Training Support in Marathon Running

Modern technology significantly influences the field of human physical exercise monitoring and control. Assuming a cybernetic-like approach to sports training, we witness a dynamic, synergistic interaction of the man-technology system realizing a training process. In this paper we focus to actual implementation of Information and Communications Technology (ICT) for intended improvement of marathon runners’ training. While general principles of sports training are known (Milanović, 2009), ICT offers profoundly novel and original possibilities to influence and actively control training process of a particular individual. First author’s sports experience (Havaš and Vlahek, 2006) is combined with an approach based on telecommunication platform which was gradually built, upgraded and validated over the years (Havaš, at al., 2013) to produce an original, comprehensive and intelligent system suited to individualized use (Havaš, 2014). Here we focus in particular to machine learning features of the approach enabling a flexible, on line physiologically based-monitoring training support system for marathon running. Developed, tested and validated on marathon runners’ data, the system however posesses capabilities for application in sports training in general. The results that were achieved by the users show that it is possible to, in such manner, achieve expected (or better) results in a single training process that lasts several months. With the assistance of realized system, it is possible to achieve the results in one season that are better than previous attempts done by the analyzed users. The probability of achieving inadequate results or an occurrence of sport injury is significantly decreased, while the probability of achieving imagined results in the suitable conditions is increased. )

Machine Learning ; Information and Communications Technology ; Data Mining ; OLAP ; Marathon Running

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