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EEG-based workload estimation across affective contexts

Mühl, C. and Jeunet, Camille and Lotte, Fabien (2014) EEG-based workload estimation across affective contexts. Frontiers in Neuroscience, 8 (114), pp. 1-15. Frontiers Media S.A.. DOI: 10.3389/fnins.2014.00114 ISSN 1662-4548

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Workload estimation from electroencephalographic signals (EEG) offers a highly sensitive tool to adapt the human–computer interaction to the user state. To create systems that reliably work in the complexity of the real world, a robustness against contextual changes (e.g., mood), has to be achieved. To study the resilience of state-of-the-art EEG-based workload classification against stress we devise a novel experimental protocol, in which we manipulated the affective context (stressful/non-stressful) while the participant solved a task with two workload levels. We recorded self-ratings, behavior, and physiology from 24 participants to validate the protocol. We test the capability of different, subject-specific workload classifiers using either frequency-domain, time-domain, or both feature varieties to generalize across contexts. We show that the classifiers are able to transfer between affective contexts, though performance suffers independent of the used feature domain. However, cross-context training is a simple and powerful remedy allowing the extraction of features in all studied feature varieties that are more resilient to task-unrelated variations in signal characteristics. Especially for frequency-domain features, across-context training is leading to a performance comparable to within-context training and testing. We discuss the significance of the result for neurophysiology-based workload detection in particular and for the construction of reliable passive brain–computer interfaces in general.

Item URL in elib:https://elib.dlr.de/92124/
Document Type:Article
Title:EEG-based workload estimation across affective contexts
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mühl, C.christian.muehl (at) dlr.deUNSPECIFIED
Journal or Publication Title:Frontiers in Neuroscience
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3389/fnins.2014.00114
Page Range:pp. 1-15
Publisher:Frontiers Media S.A.
Keywords:workload, stress, brain–computer interface, classification, electroencephalography, passive brain computer interface
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Human factors and safety in Aeronautics
Location: Köln-Porz
Institutes and Institutions:Institute of Aerospace Medicine > Flight Physiology
Deposited By: Martin, Sophie
Deposited On:03 Dec 2014 11:10
Last Modified:14 Dec 2019 04:22

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