Controlling a Nursing Robot Based on sEMG Signal

Abstract

Biopotential signals such as surface electromyography (sEMG) are common signals that can be used to control machines such as medical and nursing robots. The main objective of this paper is to develop a system to control a nursing robot using a sEMG signal. The robot was designed based on the Asian adult hand using CATIA and manufactured using a 3D printing machine. This robot was designated as a care robot to replace and assist physiotherapists in their work, especially in repetitive tasks. The sEMG signal was used as input to control the movement of the care robot. The raw signal from the sEMG was filtered to avoid the noise signal and irrelevant signals were to be rejected. In this project, the MyoWare muscle sensor attached to electrodes on the upper limbs was used to capture the EMG signal. The different readings of the signal are used as an algorithm for the movement of the care robot. As an actuator, the servo motor was operated in two positions: Flexion and extension in 0 degrees (minimum angle) to 100 degrees (maximum angle). The result shows that the robot can only move up and down in one direction with the right hand. This method is similar to the work that therapists do for their patients, especially in rehabilitation.