Fatigue driving is one of the leading causes of traffic accidents, so fatigue driving detection
technology plays a crucial role in road safety. The physiological information-based fatigue …

Electroencephalography (EEG) signal has been recognized as an effective fatigue detection
method, which can intuitively reflect the drivers' mental state. However, the research on multi …

Detecting driver fatigue is critical for ensuring traffic safety. Electroencephalography (EEG) is
the golden standard for brain activity measurement and is considered a good indicator of …

Electroencephalography (EEG) signals have been proven to be one of the most predictive
and reliable indicators for estimating driving fatigue state. However, how to make full use of …

Driver fatigue is an important cause of traffic accidents, which has triggered great concern for
detecting drivers' fatigue. Numerous methods have been proposed to fulfill this challenging …

Fatigue detection for drivers in public transportation is crucial. To effectively detect the
driver's fatigue state, we investigated the deep learning-based fatigue detection method and …

Fatigue driving has become one of the main causes of traffic accidents, and driving fatigue
detection based on electroencephalogram (EEG) can effectively evaluate the driver's mental …

Deep neural networks have recently been successfully extended to EEG-based driving
fatigue detection. Nevertheless, most existing models fail to reveal the intrinsic inter-channel …

Fatigued driving is a leading cause of traffic accidents, and accurately predicting driver
fatigue can significantly reduce their occurrence. However, modern fatigue detection models …

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 …