A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning
Driver fatigue is an essential reason for traffic accidents, which poses a severe threat to
people's lives and property. In this review, we summarize the latest research findings and …
people's lives and property. In this review, we summarize the latest research findings and …
A driving fatigue feature detection method based on multifractal theory
F Wang, H Wang, X Zhou, R Fu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Driving fatigue seriously threatens traffic safety. In our work, the multifractal detrended
fluctuation analysis (MF-DFA) method is proposed to detect driver fatigue caused by driving …
fluctuation analysis (MF-DFA) method is proposed to detect driver fatigue caused by driving …
[PDF][PDF] Recent Advances in Fatigue Detection Algorithm Based on EEG.
F Wang, Y Wan, M Li, H Huang, L Li… - … Automation & Soft …, 2023 - cdn.techscience.cn
Fatigue is a state commonly caused by overworked, which seriously affects daily work and
life. How to detect mental fatigue has always been a hot spot for researchers to explore …
life. How to detect mental fatigue has always been a hot spot for researchers to explore …
Tetromino pattern based accurate EEG emotion classification model
Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …
[HTML][HTML] EEG-based driving fatigue detection using multilevel feature extraction and iterative hybrid feature selection
Brain activities can be evaluated by using Electroencephalogram (EEG) signals. One of the
primary reasons for traffic accidents is driver fatigue, which can be identified by using EEG …
primary reasons for traffic accidents is driver fatigue, which can be identified by using EEG …
EEG Signal denoising using hybrid approach of Variational Mode Decomposition and wavelets for depression
Background Artifact contamination reduces the accuracy of various EEG based
neuroengineering applications. With time, biomedical signal denoising has been the utmost …
neuroengineering applications. With time, biomedical signal denoising has been the utmost …
EEG-based driver fatigue detection using FAWT and multiboosting approaches
Globally, 14%–20% of road accidents are mainly due to driver fatigue, the causes of which
are instance sickness, travelling for long distance, boredom as a result of driving along the …
are instance sickness, travelling for long distance, boredom as a result of driving along the …
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 …
Motion artifacts suppression from EEG signals using an adaptive signal denoising method
Motion artifacts are one of the most challenging non-physiological noise sources present in
the biomedical signal, which can hinder the true performance of EEG-based neuro …
the biomedical signal, which can hinder the true performance of EEG-based neuro …
[HTML][HTML] Research on a real-time driver fatigue detection algorithm based on facial video sequences
The research on driver fatigue detection is of great significance to improve driving safety.
This paper proposes a real-time comprehensive driver fatigue detection algorithm based on …
This paper proposes a real-time comprehensive driver fatigue detection algorithm based on …