Juggling 4.0: Learning Complex Motor Skills with Augmented Reality Through the Example of Juggling

Abstract

Learning new motor skills is a problem that people are constantly confronted with (e.g. to learn a new kind of sport). In our work, we investigate to which extent the learning process of a motor sequence can be optimized with the help of Augmented Reality as a technical assistant. Therefore, we propose an approach that divides the problem into three tasks: (1) the tracking of the necessary movements, (2) the creation of a model that calculates possible deviations and (3) the implementation of a visual feedback system. To evaluate our approach, we implemented the idea by using infrared depth sensors and an Augmented Reality head-mounted device (HoloLens). Our results show that the system can give an efficient assistance for the correct height of a throw with one ball. Furthermore, it provides a basis for the support of a complete juggling sequence.