Joint angle estimation system for rehabilitation evaluation support

In this research, we propose a methodology for getting joint angles by Kinect sensor for rehabilitation evaluation support. We measure the motion of the arm of a patient with hemiplegia before and after the rehabilitation, and estimate the range of the motion by using genetic algorithm and neural network. The range after the rehabilitation is bigger than before the rehabilitation. Based on this result, our methodology is able to evaluate the change of the motion before and after the rehabilitation for patients with hemiplegia.