Auto-adaptive robot-aided therapy using machinelearning techniques

Abstract

This paper presents an application of a classification method to adaptively and dynamicallymodify the therapy and real-time displays of a virtual reality system in accordance with thespecific state of each patient using his/her physiological reactions. First, a theoretical back-ground about several machine learning techniques for classification is presented. Then, ninemachine learning techniques are compared in order to select the best candidate in terms ofaccuracy. Finally, first experimental results are presented to show that the therapy can bemodulated in function of the patient state using machine learning classification techniques.