Surface electromyogram (sEMG) detection and analysis in the development of an Exoskeleton Control System

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.