Machine learning and applications for brain-computer Interfacing

Klaus Muller, M. Krauledat, G. Dornhege, G. Curio, B. Blankertz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper discusses machine learning methods and their application to Brain-Computer Interfacing. A particular focus is placed on linear classification methods which can be applied in the BCI context. Finally, we provide an overview on the Berlin-Brain Computer Interface (BBCI).

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages705-714
Number of pages10
Volume4557 LNCS
EditionPART 1
Publication statusPublished - 2007 Dec 1
Externally publishedYes
EventSymposium on Human Interface 2007 - Beijing, China
Duration: 2007 Jul 222007 Jul 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4557 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherSymposium on Human Interface 2007
CountryChina
CityBeijing
Period07/7/2207/7/27

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ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Muller, K., Krauledat, M., Dornhege, G., Curio, G., & Blankertz, B. (2007). Machine learning and applications for brain-computer Interfacing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 4557 LNCS, pp. 705-714). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4557 LNCS, No. PART 1).