Title :
Robot assisted stroke rehabilitation: Estimation of muscle force/joint torque from EMG using GA
Author :
Oyong, ArifWicaksana ; Parasuraman, S. ; Jauw, Veronica Lestari
Author_Institution :
Sch. of Eng., Monash Univ., Bandar Sunway, Malaysia
fDate :
Nov. 30 2010-Dec. 2 2010
Abstract :
This project focuses on the development of robot-assisted stroke rehabilitation by implementing electromyography (EMG) as the interface between robot and user communication. Key issue in implementation of EMG in this application is conversion of EMG signal into torque data. This paper presents a methodology of EMG signal to estimated joint torque conversion by using genetic algorithm (GA). Basic principle of GA, formulation, and implementation to the problem are discussed in this paper. Experimentation with real life EMG data has been carried out to assess the feasibility of the methodology in robot-assisted stroke rehabilitation problem. Preliminary investigations show that the methodology can be used in EMG to joint torque conversion algorithm.
Keywords :
biomechanics; diseases; electromyography; genetic algorithms; medical robotics; medical signal processing; patient rehabilitation; user interfaces; EMG; conversion algorithm; electromyography; genetic algorithm; muscle force-joint torque estimation; robot assisted stroke rehabilitation; user-robot interface communication; Biological cells; Elbow; Electromyography; Gallium; Genetics; Muscles; Torque; Stroke rehabilitation; electromyography (EMG); genetic algorithm (GA); robotics;
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7599-5
DOI :
10.1109/IECBES.2010.5742257