EEG Controlled Automated Writing Robotic Arm Based on Steady State Visually Evoked Potential

Abstract

Brain-Computer Interface(BCI) refers to devices that allow people to communicate or control the outside devices only through brain waves without relying on their own output pathways, such as the human nervous system and muscle tissue. The problem of insufficient information transfer and interaction between organism and electromechanical device in electromechanical integration system is pointed out. This paper uses BP(Brain Products) equipment to collect Steady State Visual Evoked Potential (SSVEP) signals. The collected SSVEP signals were preprocessed, feature extracted and feature classified. Then it is connected with the robot arm to build a portable brain-computer interface control system. Six subjects participated in the online experiment of the system. Experimental results show that the system can write some simple Chinese characters with high accuracy, and the system is feasible and effective. Then the signal is taken by Open Brain-computer Interface (OpenBCI) to complete the connection with the robotic arm. We will realize the control of the robotic arm in the later experiment. Our research aim is to find an relatively effective control method by comparing BP and OpenBCI based control on the robotic arm.