Online detection of error-related potentials boosts the performance of mental typewriters

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dc.contributor.authorSchmidt, Nico M.en
dc.contributor.authorBlankertz, Benjaminen
dc.contributor.authorTreder, Matthias S.en
dc.date.accessioned2015-11-21T00:57:00Z
dc.date.available2015-08-07T12:00:00Z
dc.date.issued2012
dc.date.submitted2015-08-06
dc.description.abstractBackground: Increasing the communication speed of brain-computer interfaces (BCIs) is a major aim of current BCI-research. The idea to automatically detect error-related potentials (ErrPs) in order to veto erroneous decisions of a BCI has been existing for more than one decade, but this approach was so far little investigated in online mode. Methods: In our study with eleven participants, an ErrP detection mechanism was implemented in an electroencephalography (EEG) based gaze-independent visual speller. Results: Single-trial ErrPs were detected with a mean accuracy of 89.1% (AUC 0.90). The spelling speed was increased on average by 49.0% using ErrP detection. The improvement in spelling speed due to error detection was largest for participants with low spelling accuracy. Conclusion: The performance of BCIs can be increased by using an automatic error detection mechanism. The benefit for patients with motor disorders is potentially high since they often have rather low spelling accuracies compared to healthy people.en
dc.identifier.eissn1471-2202
dc.identifier.uriurn:nbn:de:kobv:83-opus4-70169
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/4910
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-4613
dc.languageEnglishen
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/2.0/en
dc.subject.ddc610 Medizin und Gesundheiten
dc.subject.otherbrain-computer interfaceen
dc.subject.otherelectroencephalographyen
dc.subject.otherERP-Spelleren
dc.subject.othererror-related potentialsen
dc.subject.otherinformation transfer rateen
dc.titleOnline detection of error-related potentials boosts the performance of mental typewritersen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber19en
dcterms.bibliographicCitation.doi10.1186/1471-2202-13-19en
dcterms.bibliographicCitation.journaltitleBMC Neuroscienceen
dcterms.bibliographicCitation.originalpublishernameBioMed Centralen
dcterms.bibliographicCitation.originalpublisherplaceLondonen
dcterms.bibliographicCitation.volume13en
tub.accessrights.dnbfree*
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatikde
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.instituteInst. Softwaretechnik und Theoretische Informatikde
tub.identifier.opus47016
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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