Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cr...

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Détails bibliographiques
Auteurs principaux: Ryan Hefron, Brett Borghetti, Christine Schubert Kabban, James Christensen, Justin Estepp
Format: Article
Langue:English
Publié: MDPI AG 2018-04-01
Collection:Sensors
Sujets:
convolutional
recurrent
neural network
cognitive workload
MATB
EEG
cross-participant
mental workload
temporal specificity
ensemble
Accès en ligne:http://www.mdpi.com/1424-8220/18/5/1339

Internet

http://www.mdpi.com/1424-8220/18/5/1339

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