Sleep, circadian rhythms and health
RG Foster - Interface Focus, 2020 - royalsocietypublishing.org
At the core of human thought, for the majority of individuals in the developed nations at least,
there is the tacit assumption that as a species we are unfettered by the demands imposed by …
there is the tacit assumption that as a species we are unfettered by the demands imposed by …
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 …
Human-machine shared driving: Challenges and future directions
Distraction, misjudgement and driving mistakes can significantly affect a driver, resulting in
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
Stretchable, transparent triboelectric nanogenerator as a highly sensitive self-powered sensor for driver fatigue and distraction monitoring
The ever-increasing automobiles have caused large number of traffic accidents every year.
Fatigue driving and distracted driving are two main reasons for most of traffic accidents …
Fatigue driving and distracted driving are two main reasons for most of traffic accidents …
Developing a deep neural network for driver fatigue detection using EEG signals based on compressed sensing
In recent years, driver fatigue has become one of the main causes of road accidents. As a
result, fatigue detection systems have been developed to warn drivers, and, among the …
result, fatigue detection systems have been developed to warn drivers, and, among the …
Automatic detection of driver fatigue based on EEG signals using a developed deep neural network
In recent years, detecting driver fatigue has been a significant practical necessity and issue.
Even though several investigations have been undertaken to examine driver fatigue, there …
Even though several investigations have been undertaken to examine driver fatigue, there …
A new dispersion entropy and fuzzy logic system methodology for automated classification of dementia stages using electroencephalograms
JP Amezquita-Sanchez, N Mammone… - Clinical Neurology and …, 2021 - Elsevier
A new EEG-based methodology is presented for differential diagnosis of the Alzheimer's
disease (AD), Mild Cognitive Impairment (MCI), and healthy subjects employing the discrete …
disease (AD), Mild Cognitive Impairment (MCI), and healthy subjects employing the discrete …
Tractor assistant driving control method based on EEG combined with RNN-TL deep learning algorithm
Nowadays, fieldwork is often accompanied by tight schedules, which tends to strain the
shoulder muscles due to high-intensity work. Moreover, it is difficult and stressful for the …
shoulder muscles due to high-intensity work. Moreover, it is difficult and stressful for the …
Fatigue driving recognition based on deep learning and graph neural network
Z Lin, T Qiu, P Liu, L Zhang, S Zhang, Z Mu - Biomedical Signal Processing …, 2021 - Elsevier
The performance of traditional fatigue driving recognition model is greatly reduced under
noisy environment. In order to solve this problem, a fatigue driving recognition framework …
noisy environment. In order to solve this problem, a fatigue driving recognition framework …
Cross-subject motor imagery tasks EEG signal classification employing multiplex weighted visibility graph and deep feature extraction
This letter presents a novel technique for classification of motor imagery (MI)
electroencephalogram (EEG) signals employing a multiplex weighted visibility graph …
electroencephalogram (EEG) signals employing a multiplex weighted visibility graph …