Cluster Analysis of Canonical Correlation Coefficients for the SSVEP Based Brain-Computer Interfaces

被引：0
作者：
Poryzala, Pawel [1 ]
Materka, Andrzej [1 ]
Byczuk, Marcin [1 ]
机构：
[1] Tech Univ Lodz, Inst Elect, Lodz, Poland
来源：
2012 JOINT CONFERENCE NEW TRENDS IN AUDIO & VIDEO AND SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, & APPLICATIONS (NTAV-SPA 2012) | 2012年
关键词：
Brain-Computer Interface (BCI); Electroencephalogram (EEG); Steady-State Visual Evoked Potential (SSVEP) detection;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, a novel method for detecting steadystate visual evoked potentials (SSVEP) using multiple channel electroencephalogram (EEG) data is presented. Accurate asynchronous detection, high speed and high information transfer rate can be achieved after a short calibration session. Spatial filtering based on the Canonical Corelation Analysis method proposed in [1] is used for identifying optimal combinations of electrode signals that cancel strong interference signals in the EEG. Data from a test group consisting of 21 subjects are used to evaluate the new methods and to compare results to standard spectrum analysis approach. Conducted research, for different length signal segments and five visual frequencies, showed improvement of both classification accuracy and detection speed.
引用
收藏
页码：149 / 154
页数：6
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