Title :
Joint angle estimation system for rehabilitation evaluation support
Author :
Kusaka, Junya ; Obo, Takenori ; Botzheim, Janos ; Kubota, Naoyuki
Author_Institution :
Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan
Abstract :
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.
Keywords :
genetic algorithms; image sensors; medical computing; neural nets; patient rehabilitation; Kinect sensor; genetic algorithm; hemiplegia patient; joint angle estimation system; neural network; patient rehabilitation; rehabilitation evaluation support; Artificial neural networks; Elbow; Estimation; Genetic algorithms; Joints; Shoulder; Three-dimensional displays;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891859
