Development of P300 Detection Algorithm for Brain Computer Interface in Single Trial

Author

Ishita, Hiroyuki ; Sakai, Motoki ; Watanabe, Jinei ; Chen, Wenxi ; Wei, Daming

Author_Institution

Univ. of Aizu, Aizu-Wakamatsu

fYear

2007

fDate

16-19 Oct. 2007

Firstpage

1100

Lastpage

1105

Abstract

This paper proposed a combinational method to estimate and discriminate the P300 component. The Kalman filter and the wavelet transformation were used to estimate the P300 component and PCA and three discrimination methods; linear discrimination analysis, Mahalanobis distance, and Bayes´ theorem, were used to discriminate the estimated P300 from single trial. The results show the effectiveness of the combinational technique in discrimination. The combination of wavelet transformation and a linear discrimination analysis can perform discrimination in the highest accuracy and the fastest processing speed.

Keywords

Bayes methods; Kalman filters; bioelectric potentials; electroencephalography; handicapped aids; medical signal processing; principal component analysis; signal detection; wavelet transforms; Bayes theorem; EEG; Kalman filter; Mahalanobis distance; P300 component detection algorithm; PCA; brain computer interface; event related potential; linear discrimination analysis; wavelet transformation; Brain computer interfaces; Computer interfaces; Detection algorithms; Electrodes; Electroencephalography; Enterprise resource planning; Filtering; Information technology; Principal component analysis; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on

Conference_Location

Aizu-Wakamatsu, Fukushima

Print_ISBN

978-0-7695-2983-7

Type

conf

DOI

10.1109/CIT.2007.101

Filename

4385232