This paper presents an EEG-based driver drowsiness estimation method using deep learning and attention mechanism. First of all, an 8-channels EEG collection hat ...
Detailed analysis of EEG signals is very helpful to improve the drowsiness detection accuracy, and provide information for drivers to drive safely. To reduce ...
It achieves an average accuracy of 97.6% in detecting sleep and is more affordable, time-efficient, and less complex compared to similar existing approaches ...
An EEG-based driver drowsiness estimation method using deep learning and attention mechanism and an early warning module designed to sound an alarm if the ...
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This section reviews the recent literature about EEG-based driver drowsiness estimation, few-shot learning algorithms, and attention-based neural networks. 2.1 ...
We propose an EEG signal detection model (MATCN-GT) that can achieve end-to-end fatigue driving detection. •. We propose a multi-scale attention temporal ...
Aug 25, 2024 · A robust and efficient eeg-based drowsiness detection system using different machine learning algorithms. Ain Shams engineering journal, 14 ...
Jun 24, 2022 · In this study, we examined the possibility of extracting features from the EEG ocular artifacts themselves to perform classification between alert and drowsy ...
A novel drivers drowsiness detection system using the techniques of deep learning, mobile computing, wearable device and Electroencephalography
Mar 1, 2024 · The present work describes a study carried out for the implementation of an automatic sleep staging using the electroencephalogram – EEG signals ...