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

fYear

2010

fDate

18-21 Aug. 2010

Firstpage

54

Lastpage

57

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);

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference 2010, Proceedings of

Conference_Location

Taipei

Print_ISBN

978-1-4244-7642-8

Type

conf

Filename

5602469