Title :
Feature extraction of visual evoked potentials using state-space model
Author :
Irie, Jun ; Yamaguchi, Tomonari ; Omori, Kana ; Inoue, Katsuhiro
Author_Institution :
Dept. of Inf. Technol., Kyushu Inst. of Technol., Fukuoka, Japan
Abstract :
Recently, there are many studies on brain computer interface (BCI) system and some use EEG response at oddball paradigms. The aim of this study is to extract the features from the EEG signal speedy and safety. In this paper, we construct the state-space model of the EEG signal, and report the results to extract the features from the EEG signal included (or not included) VEP. It is confirmed that a significant difference about signal-to-noise ratio (SNR) between the measured EEG signal included VEP and one not included VEP. Effective information is obtained from the EEG signal near of the occipital area.
Keywords :
brain-computer interfaces; electroencephalography; feature extraction; medical signal processing; BCI; EEG; SNR; brain computer interface; feature extraction; signal-to-noise ratio; state-space model; visual evoked potentials; Brain modeling; Electroencephalography; Feature extraction; Kalman filters; Signal to noise ratio; Visualization; Kalman Filter; State-Space Modeling; brain computer interface (BCI); visual evoked potentials (VEP);
Conference_Titel :
SICE Annual Conference 2010, Proceedings of
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7642-8
