Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving

dc.contributor.authorZander, Thorsten O.
dc.contributor.authorAndreessen, Lena M.
dc.contributor.authorBerg, Angela
dc.contributor.authorBleuel, Maurice
dc.contributor.authorPawlitzki, Juliane
dc.contributor.authorZawallich, Lars
dc.contributor.authorKrol, Laurens R.
dc.contributor.authorGramann, Klaus
dc.date.accessioned2019-10-23T15:09:51Z
dc.date.available2019-10-23T15:09:51Z
dc.date.issued2017-02-28
dc.date.updated2019-09-29T00:47:17Z
dc.description.abstractWe tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort.en
dc.identifier.eissn1662-5161
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10175
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9164
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc600 Technik, Technologiede
dc.subject.otherautonomous drivingen
dc.subject.otherpassive BCIen
dc.subject.otherEEGen
dc.subject.otherusabilityen
dc.subject.otherERPen
dc.titleEvaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Drivingen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber78en
dcterms.bibliographicCitation.doi10.3389/fnhum.2017.00078en
dcterms.bibliographicCitation.journaltitleFrontiers in Human Neuroscienceen
dcterms.bibliographicCitation.originalpublishernameFrontiers Media S.A.en
dcterms.bibliographicCitation.originalpublisherplaceLausanneen
dcterms.bibliographicCitation.volume11en
tub.accessrights.dnbfreeen
tub.affiliationFak. 5 Verkehrs- und Maschinensysteme::Inst. Psychologie und Arbeitswissenschaft::FG Biopsychologie und Neuroergonomiede
tub.affiliation.facultyFak. 5 Verkehrs- und Maschinensystemede
tub.affiliation.groupFG Biopsychologie und Neuroergonomiede
tub.affiliation.instituteInst. Psychologie und Arbeitswissenschaftde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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