dc.contributor.author	Somon, Bertille
dc.contributor.author	Giebeler, Yasmina
dc.contributor.author	Darmet, Ludovic
dc.contributor.author	Dehais, Frédéric
dc.date.accessioned	2022-11-08T08:55:19Z
dc.date.available	2022-11-08T08:55:19Z
dc.date.issued	2022-01-06
dc.date.updated	2022-09-04T22:42:36Z
dc.description.abstract	Transfer from experiments in the laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. In this study, we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 71.5% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenues toward detecting cognitive failures in real-life situations, such as real flight.
dc.identifier.eissn	2673-6195
dc.identifier.uri	https://depositonce.tu-berlin.de/handle/11303/17638
dc.identifier.uri	https://doi.org/10.14279/depositonce-16422
dc.language.iso	en
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject.ddc	152 Sinneswahrnehmung, Bewegung, Emotionen, Triebe	de
dc.subject.ddc	153 Kognitive Prozesse, Intelligenz	de
dc.subject.other	electroencephalography	en
dc.subject.other	machine learning	en
dc.subject.other	Riemannian Geometry	en
dc.subject.other	flight simulator	en
dc.subject.other	inattentional deafness	en
dc.subject.other	Event-Related Spectral Perturbation	en
dc.subject.other	mobile EEG	en
dc.subject.other	neuroergonomics	en
dc.subject.other	ERSP	en
dc.title	Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator
dc.type	Article
dc.type.version	publishedVersion
dcterms.bibliographicCitation.articlenumber	802486
dcterms.bibliographicCitation.doi	10.3389/fnrgo.2021.802486
dcterms.bibliographicCitation.journaltitle	Frontiers in Neuroergonomics
dcterms.bibliographicCitation.originalpublishername	Frontiers
dcterms.bibliographicCitation.originalpublisherplace	Lausanne
dcterms.bibliographicCitation.volume	2
tub.accessrights.dnb	free
tub.affiliation	Fak. 5 Verkehrs- und Maschinensysteme::Inst. Psychologie und Arbeitswissenschaft::FG Kognitionspsychologie & Kognitive Ergonomie
tub.publisher.universityorinstitution	Technische Universität Berlin

Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator

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