EEG signal processing for brain-computer interfaces

aut.publication.placeBerlin
aut.relation.chapternumber46
aut.relation.endpage812
aut.relation.pages16
aut.relation.startpage797
aut.researcherKasabov, Nikola
dc.contributor.authorGeorgieva, P
dc.contributor.authorSilva, F
dc.contributor.authorMilanova, M
dc.contributor.authorKasabov, N
dc.date.accessioned2014-03-21T00:40:23Z
dc.date.available2014-03-21T00:40:23Z
dc.date.copyright2014
dc.date.issued2014
dc.description.abstractThis chapter is focused on recent advances in electroencephalogram (EEG) signal processing for brain computer interface (BCI) design. A general overview of BCI technologies is first presented, and then the protocol for motor imagery noninvasive BCI for mobile robot control is discussed. Our ongoing research on noninvasive BCI design based not on recorded EEG but on the brain sources that originated the EEG signal is also introduced. We propose a solution to EEG-based brain source recovering by combining two techniques, a sequential Monte Carlo method for source localization and spatial filtering by beamforming for the respective source signal estimation. The EEG inverse problem is previously studded assuming that the source localization is known. In this work for the first time the problem of inverse modeling is solved simultaneously with the problem of the respective source space localization.
dc.identifier.citationSpringer Handbook of Bio-/Neuroinformatics (2014), pp 797-812
dc.identifier.doi10.1007/978-3-642-30574-0
dc.identifier.isbn978-3-642-30573-3
dc.identifier.urihttps://hdl.handle.net/10292/6989
dc.publisherSpringer-Verlag
dc.relation.urihttp://dx.doi.org/10.1007/978-3-642-30574-0
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.rights.accessrightsOpenAccess
dc.titleEEG signal processing for brain-computer interfaces
dc.typeChapter in Book
pubs.elements-id149088
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
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