Measuring and computing cognitive statuses of construction workers based on electroencephalogram: a critical review

B Cheng, C Fan, H Fu, J Huang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Construction workers' cognitive statuses affecting their safety and productivity are essential
for successful construction management. Electroencephalogram (EEG) provides a potential …

Electroencephalography (EEG) technology applications and available devices

M Soufineyestani, D Dowling, A Khan - Applied Sciences, 2020 - mdpi.com
The electroencephalography (EEG) sensor has become a prominent sensor in the study of
brain activity. Its applications extend from research studies to medical applications. This …

Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions

S Latif, M Driss, W Boulila, ZE Huma, SS Jamal… - Sensors, 2021 - mdpi.com
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …

Wearable flexible electronics based cardiac electrode for researcher mental stress detection system using machine learning models on single lead electrocardiogram …

MB Bin Heyat, F Akhtar, SJ Abbas, M Al-Sarem… - Biosensors, 2022 - mdpi.com
In the modern world, wearable smart devices are continuously used to monitor people's
health. This study aims to develop an automatic mental stress detection system for …

Self-paced dynamic infinite mixture model for fatigue evaluation of pilots' brains

EQ Wu, M Zhou, D Hu, L Zhu, Z Tang… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Current brain cognitive models are insufficient in handling outliers and dynamics of
electroencephalogram (EEG) signals. This article presents a novel self-paced dynamic …

[HTML][HTML] Multimodal integration for data-driven classification of mental fatigue during construction equipment operations: Incorporating electroencephalography …

I Mehmood, H Li, W Umer, A Arsalan, S Anwer… - Developments in the …, 2023 - Elsevier
Construction equipment operations that require high levels of attention can cause mental
fatigue, which can lead to inefficiencies and accidents. Previous studies classified mental …

Towards safe and collaborative aerodrome operations: Assessing shared situational awareness for adverse weather detection with EEG-enabled Bayesian neural …

CY Yiu, KKH Ng, X Li, X Zhang, Q Li, HS Lam… - Advanced Engineering …, 2022 - Elsevier
Teams formulated by aviation professionals are essential in maintaining a safe and efficient
aerodrome environment. Nonetheless, the shared situational awareness between the flight …

LieNet: A deep convolution neural network framework for detecting deception

M Karnati, A Seal, A Yazidi… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Nowadays, automatic deception detection has received considerable attention in the
machine learning community owing to this research interest to its vast applications in the …

Driver distraction detection using bidirectional long short-term network based on multiscale entropy of EEG

X Zuo, C Zhang, F Cong, J Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Driver distraction diverting drivers' attention to unrelated tasks and decreasing the ability to
control vehicles, has aroused widespread concern about driving safety. Previous studies …

CSF-GTNet: A novel multi-dimensional feature fusion network based on Convnext-GeLU-BiLSTM for EEG-signals-enabled fatigue driving detection

D Gao, P Li, M Wang, Y Liang, S Liu… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Electroencephalography (EEG) signal has been recognized as an effective fatigue detection
method, which can intuitively reflect the drivers' mental state. However, the research on multi …