Mapping Three Electromyography Signals Generated by Human Elbow and Shoulder Movements to Two Degree of Freedom Upper-Limb Robot Control

Abstract

This article sought to address issues related to human-robot cooperation tasks focusing especially on robotic operation using bio-signals. In particular, we propose to develop a control scheme for a robot arm based on electromyography (EMG) signal that allows a cooperative task between humans and robots that would enable teleoperations. A basic framework for achieving the task and conducting EMG signals analysis of the motion of upper limb muscles for mapping the hand motion is presented. The objective of this work is to investigate the application of a wearable EMG device to control a robot arm in real-time. Three EMG sensors are attached to the brachioradialis, biceps brachii, and anterior deltoid muscles as targeted muscles. Three motions were conducted by moving the arm about the elbow joint, shoulder joint, and a combination of the two joints giving a two degree of freedom. Five subjects were used for the experiments. The results indicated that the performance of the system had an overall accuracy varying from 50% to 100% for the three motions for all subjects. This study has further shown that upper-limb motion discrimination can be used to control the robotic manipulator arm with its simplicity and low computational cost.