Control of a 7-DOF Robotic Arm System With an SSVEP-Based BCI

Author:

Chen Xiaogang1,Zhao Bing1,Wang Yijun2,Xu Shengpu1,Gao Xiaorong3

Affiliation:

1. Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, P. R. China

2. State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, P. R. China

3. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, P. R. China

Abstract

Although robot technology has been successfully used to empower people who suffer from motor disabilities to increase their interaction with their physical environment, it remains a challenge for individuals with severe motor impairment, who do not have the motor control ability to move robots or prosthetic devices by manual control. In this study, to mitigate this issue, a noninvasive brain-computer interface (BCI)-based robotic arm control system using gaze based steady-state visual evoked potential (SSVEP) was designed and implemented using a portable wireless electroencephalogram (EEG) system. A 15-target SSVEP-based BCI using a filter bank canonical correlation analysis (FBCCA) method allowed users to directly control the robotic arm without system calibration. The online results from 12 healthy subjects indicated that a command for the proposed brain-controlled robot system could be selected from 15 possible choices in 4[Formula: see text]s (i.e. 2[Formula: see text]s for visual stimulation and 2[Formula: see text]s for gaze shifting) with an average accuracy of 92.78%, resulting in a 15 commands/min transfer rate. Furthermore, all subjects (even naive users) were able to successfully complete the entire move-grasp-lift task without user training. These results demonstrated an SSVEP-based BCI could provide accurate and efficient high-level control of a robotic arm, showing the feasibility of a BCI-based robotic arm control system for hand-assistance.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Networks and Communications,General Medicine

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