Machine learning for performance management of robot-assisted cerebral palsy training system

Machine learning algorithms are applied for measuring the performance of robot-assisted cerebral palsy rehabilitation training system. Such approach allows an analysis and predictions about the system reaction to be done with high accuracy. The rehabilitation training actions of children with cerebral palsy are focused on imagination and conscious control of the face, such as left or right exercises. The aim of the designed interface interaction module is to motivate and to improve the training enthusiasm of the children with cerebral palsy to continue with the rehabilitation therapy avoiding the thoughts about the pain, tiredness and discomfort. The robot is simulated in the platform CopeliaSim.