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

• Main Authors: Cui, Jian, Lan, Zirui, Liu, Yisi, Li, Ruilin, Li, Fan, Sourina, Olga, Müller-Wittig, Wolfgang
• Other Authors: Fraunhofer Singapore
• Format: 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
• Institution: Nanyang Technological University

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...