Title: Design and implementation of a brain-computer interface based on virtual instrumentation

Authors: Genghuang Yang, Longteng Xiao, Hui Shen, Yan Bian, Li Zhao, Shigang Cui

Addresses: School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China. ' School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China. ' School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China. ' School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China. ' School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China. ' School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, PC300222, China

Abstract: The paper presents an on-line brain-computer interface (BCI) based on visual evoked potential (VEP) P300. The BCI is applied to control a multi-DOF manipulator. This BCI system includes five modules which are visual stimulator, signal acquisition, data processing, communication and motion control of the manipulator. In the experiment, the subject chooses the right oddball on a CRT/LCD displayer with eight blocks which are corresponding to the actions of the manipulator and gazes at it. The electroencephalography (EEG) of the subject is sampled to extract P300 feature. The algorithms of peak extraction, correlation analysis and wavelet transform are used to analyse EEG. The manipulator is controlled to move or operate by the subject|s EEG with wire or wireless communication. The experiments show that the subject with little training can control the manipulator. The application and the future improvement of the research are also available in the paper.

Keywords: brain-computer interface; BCI; visual evoked potential; VEP; P300; wavelet transform; manipulator control; virtual instrumentation; robot control; visual stimulation; signal acquisition; data processing; robot communications; motion control; electroencephalography; EEG.

DOI: 10.1504/IJAMECHS.2010.030847

International Journal of Advanced Mechatronic Systems, 2010 Vol.2 No.1/2, pp.36 - 45

Published online: 10 Jan 2010 *

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