Temporally Regularized Filters for Common Spatial Patterns by Preserving Locally Linear Structure of EEG Trials

Common spatial patterns (CSP) is a commonly used method of feature extraction for motor imagery–based brain computer interfaces (BCI). However, its performance is limited when subjects have small training samples or signals are very noisy. In this paper, we propose a new regularized CSP: temporally...

Full description

Saved in:
Bibliographic Details
Published inNeural Information Processing pp. 167 - 174
Main Authors Cheng, Minmin, Wang, Haixian, Lu, Zuhong, Lu, Deji
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2014
SeriesLecture Notes in Computer Science
Subjects
brain–computer interfaces (BCI)
common spatial patterns (CSP)
locally linear structure
regularization
Online AccessGet full text
ISBN9783319126425
3319126423
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-12643-2_21

Cover

Abstract Common spatial patterns (CSP) is a commonly used method of feature extraction for motor imagery–based brain computer interfaces (BCI). However, its performance is limited when subjects have small training samples or signals are very noisy. In this paper, we propose a new regularized CSP: temporally regularized common spatial patterns (TRCSP), which is an extension of the conventional CSP by preserving locally linear structure. The proposed method and CSP are tested on data sets from BCI competitions. Experimental results show that the TRCSP achieves higher average accuracy for most of the subjects and some of them are up to 10%. Furthermore, the results also show that the TRCSP is particularly effective in the small–sample data sets.
AbstractList Common spatial patterns (CSP) is a commonly used method of feature extraction for motor imagery–based brain computer interfaces (BCI). However, its performance is limited when subjects have small training samples or signals are very noisy. In this paper, we propose a new regularized CSP: temporally regularized common spatial patterns (TRCSP), which is an extension of the conventional CSP by preserving locally linear structure. The proposed method and CSP are tested on data sets from BCI competitions. Experimental results show that the TRCSP achieves higher average accuracy for most of the subjects and some of them are up to 10%. Furthermore, the results also show that the TRCSP is particularly effective in the small–sample data sets.
Author Wang, Haixian
Lu, Zuhong
Lu, Deji
Cheng, Minmin
Author_xml – sequence: 1
  givenname: Minmin
  surname: Cheng
  fullname: Cheng, Minmin
  email: mmcheng@seu.edu.cn
  organization: Key Lab. of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
– sequence: 2
  givenname: Haixian
  surname: Wang
  fullname: Wang, Haixian
  email: hxwang@seu.edu.cn
  organization: Key Lab. of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
– sequence: 3
  givenname: Zuhong
  surname: Lu
  fullname: Lu, Zuhong
  email: zhlu@seu.edu.cn
  organization: Key Lab. of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
– sequence: 4
  givenname: Deji
  surname: Lu
  fullname: Lu, Deji
  email: deji.lu@gmail.com
  organization: Medical Electronics Lab., Southeast University, Nanjing, China
BookMark eNpVkMFOwzAQRA0UiVL6Bxz8AwavncTJEVVtQYpERcvZcpJ1FUjjyk6RytfjFi6cRprRjnbeLRn1rkdC7oE_AOfqsVA5k0xCwUBkiWRCC7gg02jLaJ49cUnGkAEwKZPi6l8m0hEZc8kFK1Qib8g0hA_OOUglFKRj4ja42ztvuu5I33B76Ixvv7Ghi7Yb0Adqnaczt9u5nq73ZmhNR1dmiFEfaHWkK48B_Vfbb2np6nNL2fZoPF0P_lAPB4_UWTqfL-nGx-NwR65tFJz-6YS8L-ab2TMrX5cvs6eSBQAZh1gQuUGuFDdQA-ZNJXKV5MbWqkhTYbMkKSC3jbKYNomsc5FlvC5ANhWqOH9CxG9v2Pv4HXpdOfcZNHB9oqojIi11hKTPBPWJqvwBIa5n4w
ContentType Book Chapter
Copyright Springer International Publishing Switzerland 2014
Copyright_xml – notice: Springer International Publishing Switzerland 2014
DOI 10.1007/978-3-319-12643-2_21
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
EISBN 9783319126432
3319126431
EISSN 1611-3349
Editor Wong, Kok Wai
Beng Jin, Andrew Teoh
Huang, Kaizhu
Loo, Chu Kiong
Yap, Keem Siah
Editor_xml – sequence: 1
  givenname: Chu Kiong
  surname: Loo
  fullname: Loo, Chu Kiong
  email: ckloo.um@um.edu.my
– sequence: 2
  givenname: Keem Siah
  surname: Yap
  fullname: Yap, Keem Siah
  email: yapkeem@uniten.edu.my
– sequence: 3
  givenname: Kok Wai
  surname: Wong
  fullname: Wong, Kok Wai
  email: k.wong@murdoch.edu.au
– sequence: 4
  givenname: Andrew Teoh
  surname: Beng Jin
  fullname: Beng Jin, Andrew Teoh
  email: bjteoh@yonsei.ac.kr
– sequence: 5
  givenname: Kaizhu
  surname: Huang
  fullname: Huang, Kaizhu
  email: kaizhu.huang@xjtlu.edu.cn
EndPage 174
GroupedDBID -DT
-GH
-~X
1SB
29L
2HA
2HV
5QI
875
AASHB
ABMNI
ACGFS
ADCXD
AEFIE
ALMA_UNASSIGNED_HOLDINGS
EJD
F5P
FEDTE
HVGLF
LAS
LDH
P2P
RIG
RNI
RSU
SVGTG
VI1
~02
ID FETCH-LOGICAL-s1131-3f128ae0770a1c1e8db28748afc79552f644918fd7fe5d43c82660c913dbe7783
ISBN 9783319126425
3319126423
ISSN 0302-9743
IngestDate Tue Jul 29 20:03:55 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-s1131-3f128ae0770a1c1e8db28748afc79552f644918fd7fe5d43c82660c913dbe7783
PageCount 8
ParticipantIDs springer_books_10_1007_978_3_319_12643_2_21
PublicationCentury 2000
PublicationDate 2014
PublicationDateYYYYMMDD 2014-01-01
PublicationDate_xml – year: 2014
  text: 2014
PublicationDecade 2010
PublicationPlace Cham
PublicationPlace_xml – name: Cham
PublicationSeriesTitle Lecture Notes in Computer Science
PublicationSubtitle 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings, Part III
PublicationTitle Neural Information Processing
PublicationYear 2014
Publisher Springer International Publishing
Publisher_xml – name: Springer International Publishing
RelatedPersons Kleinberg, Jon M.
Mattern, Friedemann
Nierstrasz, Oscar
Steffen, Bernhard
Kittler, Josef
Weikum, Gerhard
Naor, Moni
Mitchell, John C.
Terzopoulos, Demetri
Kobsa, Alfred
Pandu Rangan, C.
Kanade, Takeo
Hutchison, David
Tygar, Doug
RelatedPersons_xml – sequence: 1
  givenname: David
  surname: Hutchison
  fullname: Hutchison, David
  organization: Lancaster University, Lancaster, UK
– sequence: 2
  givenname: Takeo
  surname: Kanade
  fullname: Kanade, Takeo
  organization: Carnegie Mellon University, Pittsburgh, USA
– sequence: 3
  givenname: Josef
  surname: Kittler
  fullname: Kittler, Josef
  organization: University of Surrey, Guildford, UK
– sequence: 4
  givenname: Jon M.
  surname: Kleinberg
  fullname: Kleinberg, Jon M.
  organization: Cornell University, Ithaca, USA
– sequence: 5
  givenname: Alfred
  surname: Kobsa
  fullname: Kobsa, Alfred
  organization: University of California, Irvine, USA
– sequence: 6
  givenname: Friedemann
  surname: Mattern
  fullname: Mattern, Friedemann
  organization: ETH Zurich, Zurich, Switzerland
– sequence: 7
  givenname: John C.
  surname: Mitchell
  fullname: Mitchell, John C.
  organization: Stanford University, Stanford, USA
– sequence: 8
  givenname: Moni
  surname: Naor
  fullname: Naor, Moni
  organization: Weizmann Institute of Science, Rehovot, Israel
– sequence: 9
  givenname: Oscar
  surname: Nierstrasz
  fullname: Nierstrasz, Oscar
  organization: University of Bern, Bern, Switzerland
– sequence: 10
  givenname: C.
  surname: Pandu Rangan
  fullname: Pandu Rangan, C.
  organization: Indian Institute of Technology, Madras, India
– sequence: 11
  givenname: Bernhard
  surname: Steffen
  fullname: Steffen, Bernhard
  organization: TU Dortmund University, Dortmund, Germany
– sequence: 12
  givenname: Demetri
  surname: Terzopoulos
  fullname: Terzopoulos, Demetri
  organization: University of California, Los Angeles, USA
– sequence: 13
  givenname: Doug
  surname: Tygar
  fullname: Tygar, Doug
  organization: University of California, Berkeley, USA
– sequence: 14
  givenname: Gerhard
  surname: Weikum
  fullname: Weikum, Gerhard
  organization: Max-Planck Institute of Computer Science, Saarbrücken, Germany
SSID ssj0001372715
ssj0002792
Score 1.4369707
Snippet Common spatial patterns (CSP) is a commonly used method of feature extraction for motor imagery–based brain computer interfaces (BCI). However, its performance...
SourceID springer
SourceType Publisher
StartPage 167
SubjectTerms brain–computer interfaces (BCI)
common spatial patterns (CSP)
locally linear structure
regularization
Title Temporally Regularized Filters for Common Spatial Patterns by Preserving Locally Linear Structure of EEG Trials
URI http://link.springer.com/10.1007/978-3-319-12643-2_21
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9NAEF6FcAEOlAKivDSH3iIjb3b9OnCoIG1UpVUlUujN8mOtGrW21CQS9DfxIzuzj9hJeykXK7IiP2Y-z87zW8b2C1wUAx77lLUpPSmT0EvkWHpK5mVc4oKpQhpOPjkNp-fy-CK4GAz-9bqWVsv8S3H74FzJ_2gVz6FeaUr2EZpdXxRP4G_ULx5Rw3jccn4306yWcEkzZth5Iq1G2_XvViNdtVfmYz6pm-t6DYRfNks8zeo_PXzMVrpWsbpsuyuYc9_V73oDXYbR6uqKXHjazf6mvkXX9bCm4rumeCBLc03GiFq28TnPNJFnsyB_l_o-yEbRgBWtpXgVjImJUuiHprOlogZ1PE6ORnMtRmP7iJN58XVmqx6n7VI3k43cxhTOTvUTGVxuJTJcInMrFdpl4zYiX4Gmg6MzZ6am3QQYWneMj4zBVMagh0TTKAwtqjXS3GwAYtd7bnYJureU9LtHaNKL7ia8cUqsBU-iWA7Z04PJ8exnl9ETCG3eBV9EzWhqWOapaLLIPbUw3E_dW_SmOh-65b06vXZ_5jvsBY3EAM2qoNBesYFqdtlLJ3ewct9lz3vslq9Z24EEeiABCxJAkIABCViQgAMJ5H-hAwlYkIABCaxBAm0FCBIwIHnDzg8n829Tz-7v4S04F6iWCp2jTPlR5Ge84Couc9p9Ic6qIkqCYFyhr57wuCqjSgWlFAWGwqFfJFyUuYpQem_ZsGkb9Y5BwlVQST_LowpDXqVyGQWFLPwSA_osCcZ7bOTkl9IXu0gdXTdKOxUpSjvV0k5J2u8f9e8P7FkH549siDJQn9BTXeafLUTuAImcjLM
linkProvider Library Specific Holdings
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.title=Neural+Information+Processing&rft.au=Cheng%2C+Minmin&rft.au=Wang%2C+Haixian&rft.au=Lu%2C+Zuhong&rft.au=Lu%2C+Deji&rft.atitle=Temporally+Regularized+Filters+for+Common+Spatial+Patterns+by+Preserving+Locally+Linear+Structure+of+EEG+Trials&rft.series=Lecture+Notes+in+Computer+Science&rft.date=2014-01-01&rft.pub=Springer+International+Publishing&rft.isbn=9783319126425&rft.issn=0302-9743&rft.eissn=1611-3349&rft.spage=167&rft.epage=174&rft_id=info:doi/10.1007%2F978-3-319-12643-2_21
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0302-9743&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0302-9743&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0302-9743&client=summon