DocumentCode
227082
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
fYear
2014
fDate
6-11 July 2014
Firstpage
1456
Lastpage
1462
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-2073-0
Type
conf
DOI
10.1109/FUZZ-IEEE.2014.6891859
Filename
6891859
Link To Document