A novel combination of time phase and EEG frequency components for SSVEP-Based BCI

Authors:
Jing Jin;Yu Zhang;Xingyu Wang
Affiliations:
School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China;School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China;School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Venue:
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Year:
2011

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Abstract

The steady-state visual evoked potential (SSVEP) has been widely applied in brain-computer interfaces (BCIs), such as letter or icon selection and device control. Most of these BCIs used different flickering frequencies to evoke SSVEP with different frequency components that were used as control commands. In this paper, a novel method combining the time phase and EEG frequency components is presented and validated with nine healthy subjects. In this method, four different frequency components of EEG were classified out from four time phases. When the SSVEP is evoked and what is the frequency of the SSVEP is determined by the linear discriminant analysis (LDA) classifier in the same time to locate the target image. The results from offline analysis show that this method yields good performance both in classification accuracy and information transfer rate (ITR).