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 …
3D-STCNN: Spatiotemporal Convolutional Neural Network based on EEG 3D features for detecting driving fatigue
B Peng, D Gao, M Wang… - Journal of Data Science …, 2024 - ojs.bonviewpress.com
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 …
detection based on electroencephalogram (EEG) can effectively evaluate the driver's mental …
A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images
S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
Deep learning for detecting multi-level driver fatigue using physiological signals: A comprehensive approach
A large share of traffic accidents is related to driver fatigue. In recent years, many studies
have been organized in order to diagnose and warn drivers. In this research, a new …
have been organized in order to diagnose and warn drivers. In this research, a new …
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 …
Visual saliency and image reconstruction from EEG signals via an effective geometric deep network-based generative adversarial network
Reaching out the function of the brain in perceiving input data from the outside world is one
of the great targets of neuroscience. Neural decoding helps us to model the connection …
of the great targets of neuroscience. Neural decoding helps us to model the connection …
[HTML][HTML] Designing a practical fatigue detection system: A review on recent developments and challenges
Introduction Fatigue is considered to have a life-threatening effect on human health and it
has been an active field of research in different sectors. Deploying wearable physiological …
has been an active field of research in different sectors. Deploying wearable physiological …
Automatically identified EEG signals of movement intention based on CNN network (End-To-End)
Movement-based brain–computer Interfaces (BCI) rely significantly on the automatic
identification of movement intent. They also allow patients with motor disorders to …
identification of movement intent. They also allow patients with motor disorders to …
Customized 2D CNN Model for the Automatic Emotion Recognition Based on EEG Signals
F Baradaran, A Farzan, S Danishvar, S Sheykhivand - Electronics, 2023 - mdpi.com
Automatic emotion recognition from electroencephalogram (EEG) signals can be considered
as the main component of brain–computer interface (BCI) systems. In the previous years …
as the main component of brain–computer interface (BCI) systems. In the previous years …
A novel approach for automatic detection of driver fatigue using EEG signals based on graph convolutional networks
SZ Ardabili, S Bahmani, LZ Lahijan, N Khaleghi… - Sensors, 2024 - mdpi.com
Nowadays, the automatic detection of driver fatigue has become one of the important
measures to prevent traffic accidents. For this purpose, a lot of research has been conducted …
measures to prevent traffic accidents. For this purpose, a lot of research has been conducted …