Title :
Surface electromyogram (sEMG) detection and analysis in the development of an Exoskeleton Control System
Author :
Elamvazuthi, I. ; Ku Nurhanim, K.A.R. ; Vasant, P. ; Parasuraman, S. ; Zulika, Z. ; Ling, G.A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Technologi PETRONAS, Tronoh, Malaysia
Abstract :
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.
Keywords :
control engineering computing; electromyography; medical control systems; medical signal processing; motion control; patient rehabilitation; signal detection; torque control; MAV; RMS; bicep muscles; exoskeleton control system; mean absolute value; muscle contraction; robot movements; robot personnel; robot torque; robotic assistive technology; root mean square; sEMG analysis; sEMG detection; signal analysis; signal detection; stroke patient rehabilitation; surface electromyogram; triceps muscles; Control systems; Electromyography; Exoskeletons; Mathematical model; Muscles; Robots; Torque; Electromyography (EMG); control system; exoskeleton; mean absolute value; muscle contraction; root mean square;
Conference_Titel :
Control Conference (AUCC), 2012 2nd Australian
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-922107-63-3
