EEG-based neural networks approaches for fatigue and drowsiness detection: A survey
Drowsiness is a state of fatigue or sleepiness characterized by a strong urge to sleep. It is
correlated with a progressive decline in response time, compromised processing of …
correlated with a progressive decline in response time, compromised processing of …
[HTML][HTML] Structural analysis of driver fatigue behavior: a systematic review
H Zhang, D Ni, N Ding, Y Sun, Q Zhang, X Li - Transportation research …, 2023 - Elsevier
Fatigue is always accompany with the driving task, which have been extensively
investigated for driver monitoring and traffic safety. While many scholars dedicate to the …
investigated for driver monitoring and traffic safety. While many scholars dedicate to the …
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 …
challenging to design a calibration-free system, since EEG signals vary significantly among …
Recognising drivers' mental fatigue based on EEG multi-dimensional feature selection and fusion
Y Zhang, H Guo, Y Zhou, C Xu, Y Liao - Biomedical Signal Processing and …, 2023 - Elsevier
Detecting the mental state of a driver using electroencephalography (EEG) signals can
reduce the probability of traffic accidents. However, EEG signals are unstable and nonlinear …
reduce the probability of traffic accidents. However, EEG signals are unstable and nonlinear …
[HTML][HTML] A spectral-ensemble deep random vector functional link network for passive brain–computer interface
Randomized neural networks (RNNs) have shown outstanding performance in many
different fields. The superiority of having fewer training parameters and closed-form …
different fields. The superiority of having fewer training parameters and closed-form …
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
Objective. This review paper provides an integrated perspective of Explainable Artificial
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
Driving drowsiness detection using spectral signatures of EEG-based neurophysiology
Introduction: Drowsy driving is a significant factor causing dire road crashes and casualties
around the world. Detecting it earlier and more effectively can significantly reduce the lethal …
around the world. Detecting it earlier and more effectively can significantly reduce the lethal …
TA-MFFNet: Multi-feature fusion network for EEG analysis and driving fatigue detection based on time domain network and attention network
B Peng, Y Zhang, M Wang, J Chen, D Gao - Computational Biology and …, 2023 - Elsevier
Driving fatigue detection based on EEG signals is a research hotspot in applying brain-
computer interfaces. EEG signal is complex, unstable, and nonlinear. Most existing methods …
computer interfaces. EEG signal is complex, unstable, and nonlinear. Most existing methods …
EEG-based index for timely detecting user's drowsiness occurrence in automotive applications
Human errors are widely considered among the major causes of road accidents.
Furthermore, it is estimated that more than 90% of vehicle crashes causing fatal and …
Furthermore, it is estimated that more than 90% of vehicle crashes causing fatal and …
Artificial intelligence-enabled non-intrusive vigilance assessment approach to reducing traffic controller's human errors
To be vigilant is highly required for traffic controllers in transportation fields, such as air traffic
management, vessel traffic service, and railway management, as they need to monitor traffic …
management, vessel traffic service, and railway management, as they need to monitor traffic …