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Updated: Mar 26, 2026

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
A MUSIC-based method for SSVEP signal processing
Kun Chen1,2, Quan Liu3,4, Qingsong Ai5,2
1School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070, China.
Abstract:
The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.
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