Pattern identification of EEG during Motor Imagery using ICA
Shingo Tamatsuka, Takuro Yamaguchi, Shotaro Watanabe, T. Ishibashi, Katsuhiro Inoue, M. Fujio, Kousuke Kumamaru · Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications · 2008
The paper proposed pattern recognition method based on ICA (Independent Component Analysis) for EEG (electroencephalogram) signals during right and left hand motor imagery. ICA can separate unknown source signals from their mixture signals if they are statistically independent. Some effective features for pattern recognition appear in the separated signals with scaling adjuster. In this paper, we try to discriminate EEG signals during left and right hand motor imagery based on ICA. As a result, we obtained the prospect concerning the construction of BCI system with the reliable pattern recognition method for discrimination of motor imagery.