dc.contributor.author	Zander, Thorsten O.
dc.contributor.author	Andreessen, Lena M.
dc.contributor.author	Berg, Angela
dc.contributor.author	Bleuel, Maurice
dc.contributor.author	Pawlitzki, Juliane
dc.contributor.author	Zawallich, Lars
dc.contributor.author	Krol, Laurens R.
dc.contributor.author	Gramann, Klaus
dc.date.accessioned	2019-10-23T15:09:51Z
dc.date.available	2019-10-23T15:09:51Z
dc.date.issued	2017-02-28
dc.date.updated	2019-09-29T00:47:17Z
dc.description.abstract	We 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.eissn	1662-5161
dc.identifier.uri	https://depositonce.tu-berlin.de/handle/11303/10175
dc.identifier.uri	http://dx.doi.org/10.14279/depositonce-9164
dc.language.iso	en	en
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	en
dc.subject.ddc	600 Technik, Technologie	de
dc.subject.other	autonomous driving	en
dc.subject.other	passive BCI	en
dc.subject.other	EEG	en
dc.subject.other	usability	en
dc.subject.other	ERP	en
dc.title	Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving	en
dc.type	Article	en
dc.type.version	publishedVersion	en
dcterms.bibliographicCitation.articlenumber	78	en
dcterms.bibliographicCitation.doi	10.3389/fnhum.2017.00078	en
dcterms.bibliographicCitation.journaltitle	Frontiers in Human Neuroscience	en
dcterms.bibliographicCitation.originalpublishername	Frontiers Media S.A.	en
dcterms.bibliographicCitation.originalpublisherplace	Lausanne	en
dcterms.bibliographicCitation.volume	11	en
tub.accessrights.dnb	free	en
tub.affiliation	Fak. 5 Verkehrs- und Maschinensysteme::Inst. Psychologie und Arbeitswissenschaft::FG Biopsychologie und Neuroergonomie	de
tub.affiliation.faculty	Fak. 5 Verkehrs- und Maschinensysteme	de
tub.affiliation.group	FG Biopsychologie und Neuroergonomie	de
tub.affiliation.institute	Inst. Psychologie und Arbeitswissenschaft	de
tub.publisher.universityorinstitution	Technische Universität Berlin	en

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

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