Gamified Motor Learning Through High-Fidelity Sensor Technology
Paris Mavromoustakos Blom,
Vasileios Mylonas,
Thomas Nikodelis
et al.
Abstract:In this paper, we present a framework for gamified motor learning through the use of a serious game and highfidelity motion capture sensors. Our implementation features an Inertial Measurement Unit and a set of Force Plates in order to obtain real-time, high-frequency measurements of patients' core movements and centre of pressure displacement during physical rehabilitation sessions. The aforementioned signals enable two mechanisms, namely a) a game avatar controlled through patient motor skills and b) a rich … Show more
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