%D 2012
%O cited By 5; Conference of 2nd Australian Control Conference, AUCC 2012 ; Conference Date: 15 November 2012 Through 16 November 2012; Conference Code:100369
%J 2012 2nd Australian Control Conference, AUCC 2012
%L scholars3126
%K Control systems; Electromyography; Electronic medical equipment; Muscle; Robots, Absolute values; Assistive technology; exoskeleton; Muscle contractions; Robot movements; Root Mean Square; Stroke patients; Surface electromyogram, Robotics
%X Numerous research have been carried out to develop robotic assistive technology for rehabilitation of stroke patients. The conventional robotic assistive technology was based on pre-programmed functions by the robot personnel. This makes it difficult for stroke patients to use it effectively due to unsuitable torque and movements set by the robot. Electromyography (EMG) signal measures the muscle contraction. The EMG-based robotic assistive technology would enable the stroke patients to control the robot movement according to their own strength. In this paper, surface EMG signal detection and analysis using the root mean square (RMS) and mean absolute value (MAV) for bicep and triceps muscles are discussed in detail. This information is vital in the development of a robotics assistive control system. © 2012 Institute of Engineers.
%P 197-202
%C Sydney, NSW
%T Surface electromyogram (sEMG) detection and analysis in the development of an exoskeleton control system
%I IEEE Computer Society
%A I. Elamvazuthi
%A K.A.R. Ku Nurhanim
%A P. Vasant
%A S. Parasuraman
%A Z. Zulika
%A G.A. Ling