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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Bibliographische Detailangaben
Hauptverfasser: Ryan Hefron, Brett Borghetti, Christine Schubert Kabban, James Christensen, Justin Estepp
Format: Artikel
Sprache:English
Veröffentlicht: MDPI AG 2018-04-01
Schriftenreihe:Sensors
Schlagworte:
convolutional
recurrent
neural network
cognitive workload
MATB
EEG
cross-participant
mental workload
temporal specificity
ensemble
Online Zugang:http://www.mdpi.com/1424-8220/18/5/1339

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

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