Regularized CSP with Fisher's criterion to improve classification of single-trial ERPs for BCI

Yu Zhang, Qibin Zhao, Guoxu Zhou, Xingyu Wang, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

A brain-computer interface (BCI) based on the combination of oddball paradigm and face perception has been introduced. Such BCI mainly exploits three event-related potential (ERP) components, namely vertex positive potential (VPP), N170 and P300 instead of only P300. With different temporal and spatial distributions of the three ERP components, a regularized common spatial pattern (CSP) with Fisher's criterion (FC), named FCCSP, is proposed to extract the most discriminative features for single trial classification of ERP components. With linear discriminant analysis (LDA) classifier, the proposed FCCSP spatial filtering method yields an average classification accuracy of 95.4% on seven healthy subjects for single-trial ERP components, which outperforms no spatial filtering, the CSP and the FC.

Original languageEnglish
Title of host publicationProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Pages891-895
Number of pages5
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012 - Chongqing, China
Duration: 29 May 201231 May 2012

Publication series

NameProceedings - 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

Conference

Conference2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012
Country/TerritoryChina
CityChongqing
Period29/05/1231/05/12

Fingerprint

Dive into the research topics of 'Regularized CSP with Fisher's criterion to improve classification of single-trial ERPs for BCI'. Together they form a unique fingerprint.

Cite this