EEG-based neural networks approaches for fatigue and drowsiness detection: A survey

A Othmani, AQM Sabri, S Aslan, F Chaieb, H Rameh… - Neurocomputing, 2023 - Elsevier
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 …

Physiological-based driver monitoring systems: A scoping review

SFA Razak, S Yogarayan, AA Aziz… - Civil Engineering …, 2022 - civilejournal.org
A physiological-based driver monitoring system (DMS) has attracted research interest and
has great potential for providing more accurate and reliable monitoring of the driver's state …

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 …

Deep learning for detecting multi-level driver fatigue using physiological signals: A comprehensive approach

M Peivandi, SZ Ardabili, S Sheykhivand, S Danishvar - Sensors, 2023 - mdpi.com
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 …

Visual saliency and image reconstruction from EEG signals via an effective geometric deep network-based generative adversarial network

N Khaleghi, TY Rezaii, S Beheshti, S Meshgini… - Electronics, 2022 - mdpi.com
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 …

Automatically identified EEG signals of movement intention based on CNN network (End-To-End)

N Shahini, Z Bahrami, S Sheykhivand, S Marandi… - Electronics, 2022 - mdpi.com
Movement-based brain–computer Interfaces (BCI) rely significantly on the automatic
identification of movement intent. They also allow patients with motor disorders to …

A digital twin-based framework for damage detection of a floating wind turbine structure under various loading conditions based on deep learning approach

Z Mousavi, S Varahram, MM Ettefagh, MH Sadeghi… - Ocean …, 2024 - Elsevier
Engineering has many necessary fields, and Structural Health Monitoring (SHM) is one of
the most important of them. Sometimes in industrial environments, it is difficult and even …

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 …

Residual attention capsule network for multimodal EEG-and EOG-based driver vigilance estimation

J Pan, X Cai, D Mo, Y Yu, Y Li - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Driver vigilance estimation is essential for fatigue and traffic accident reduction. Although
previous algorithms for driver vigilance estimation have achieved high evaluation …

Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis

M Azadi Moghadam, A Maleki - Frontiers in Human Neuroscience, 2023 - frontiersin.org
Background Fatigue is a serious challenge when applying a steady-state visual evoked
potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many …