A compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel EEG

A compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel EEG

Driver drowsiness is one of the main factors leading to road fatalities and hazards in the transportation industry. Electroencephalography (EEG) has been considered as one of the best physiological signals to detect drivers' drowsy states, since it directly measures neurophysiological activitie...

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Bibliographic Details
Main Authors: Cui, Jian, Lan, Zirui, Liu, Yisi, Li, Ruilin, Li, Fan, Sourina, Olga, Müller-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
Single-Channel EEG
Driver Drowsiness Detection
Convolutional Neural Network
Online Access:https://hdl.handle.net/10356/156070

Internet

https://hdl.handle.net/10356/156070

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