Personalized training through Kinect-based games for physical education

Abstract In recent years, the Kinect-based systems that enable users to be trained without the participation of teachers have been widely used in the field of physical education. In this paper, we propose a novel technique that helps the Kinect-based training system to select the subsequential training material for the users according to their realtime performance. An algorithm based on the Hidden Markov Model is demonstrated to generate the customized training pathes(training curriculums) for each individual. We present an edutainment gaming system for children in order to illustrate the feasibility of the training method. A user study of 10 children participants is conducted and the results show that the proposed technique enhances the effect of physical training significantly.

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