Predictive Analysis of Errors During Robot-Mediated Gamified Training.

This paper presents our approach to predicting future error-related events in a robot-mediated gamified physical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishable features and separated class characteristics between the casual gameplay state and error prune state in the data. Identifying such features provides valuable insight to creating individually tailored, adaptive games as well as possible ways to increase rehabilitation success by patients.