EEG-based Cross-Subject Driver Drowsiness Recognition with an Interpretable Convolutional Neural Network

• Published in: arXiv.org
• Main Authors: Cui, Jian, Zirui Lan, Sourina, Olga, Müller-Wittig, Wolfgang
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 18.02.2022
• Subjects: Artificial neural networks; Computer Science - Learning; Computer Science - Neural and Evolutionary Computing; Deep learning; Driver fatigue; Electroencephalography; Feature recognition; Machine learning; Model accuracy; Quantitative Biology - Neurons and Cognition; Signal processing; Sleepiness; Teaching methods

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...