EEG-based cross-subject driver drowsiness recognition with an interpretable convolutional neural network

EEG-based cross-subject driver drowsiness recognition with an interpretable convolutional neural network

In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still challenging to design a calibration-free system, since EEG signals vary significantly among different subjects and recording sessions. Many efforts have been made to use deep learning methods for mental sta...

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Bibliographic Details
Main Authors: Cui, Jian, Lan, Zirui, Sourina, Olga, Muller-Wittig, Wolfgang
Other Authors: Fraunhofer Singapore
Format: Journal Article
Language:English
Published: 2022
Subjects:
Science::Biological sciences::Human anatomy and physiology
Engineering::Computer science and engineering
Convolutional Neural Network
Electroencephalography
Driver Drowsiness Recognition
Interpretable Deep Learning
Online Access:https://hdl.handle.net/10356/156069

Internet

https://hdl.handle.net/10356/156069

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