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dc.contributor.authorBrandl, Stephanie-
dc.contributor.authorHöhne, Johannes-
dc.contributor.authorMüller, Klaus-Robert-
dc.contributor.authorSamek, Wojciech-
dc.date.accessioned2020-04-08T11:21:44Z-
dc.date.available2020-04-08T11:21:44Z-
dc.date.issued2015-07-02-
dc.identifier.isbn978-1-4673-6389-1-
dc.identifier.issn1948-3546-
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10980-
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9871-
dc.description.abstractBringing Brain-Computer Interfaces (BCIs) into everyday life is a challenge because an out-of-lab environment implies the presence of variables that are largely beyond control of the user and the software application. This can severely corrupt signal quality as well as reliability of BCI control. Current BCI technology may fail in this application scenario because of the large amounts of noise, nonstationarity and movement artifacts. In this paper, we systematically investigate the performance of motor imagery BCI in a pseudo realistic environment. In our study 16 participants were asked to perform motor imagery tasks while dealing with different types of distractions such as vibratory stimulations or listening tasks. Our experiments demonstrate that standard BCI procedures are not robust to theses additional sources of noise, implicating that methods which work well in a lab environment, may perform poorly in realistic application scenarios. We discuss several promising research directions to tackle this important problem.en
dc.description.sponsorshipBMBF, 01GQ1115, Adaptive Gehirn-Computer-Schnittstellen (BCI) in nichtstationären Umgebungenen
dc.language.isoenen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.ddc006 Spezielle Computerverfahrende
dc.subject.otherbrain-computer interfaceen
dc.subject.otherBCIen
dc.subject.otherout-of-lab environmenten
dc.subject.othermotor imageryen
dc.subject.otherdistractionen
dc.subject.otherperformance evaluationen
dc.titleBringing BCI into everyday life: Motor imagery in a pseudo realistic environmenten
dc.typeConference Objecten
dc.relation.issupplementedby10.14279/depositonce-9827-
tub.accessrights.dnbfreeen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
dc.identifier.eissn1948-3554-
dc.type.versionacceptedVersionen
dcterms.bibliographicCitation.doi10.1109/NER.2015.7146600en
dcterms.bibliographicCitation.proceedingstitle2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)en
dcterms.bibliographicCitation.originalpublisherplaceNew York, NY [u.a.]en
dcterms.bibliographicCitation.originalpublishernameInstitute of Electrical and Electronics Engineers (IEEE)en
tub.affiliationFak. 4 Elektrotechnik und Informatik » Inst. Softwaretechnik und Theoretische Informatik » FG Maschinelles Lernende
Appears in Collections:Technische Universität Berlin » Publications

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