EEG-based mental workload estimation using deep BLSTM-LSTM network and evolutionary algorithm

DD Chakladar, S Dey, PP Roy, DP Dogra - Biomedical Signal Processing …, 2020 - Elsevier
The mental workload can be estimated by monitoring different mental states from neural
activity. The spectral power of EEG and Event-Related Potentials (ERPs) are the two …

Artificial intelligence modelling human mental fatigue: a comprehensive survey

A Lambert, A Soni, A Soukane, AR Cherif, A Rabat - Neurocomputing, 2024 - Elsevier
Mental fatigue refers to the decline in cognitive abilities that can occur as a result of
prolonged mental exertion. Neuroscientists have been studying mental fatigue for a while …

Cross-subject zero calibration driver's drowsiness detection: Exploring spatiotemporal image encoding of EEG signals for convolutional neural network classification

JR Paulo, G Pires, UJ Nunes - IEEE transactions on neural …, 2021 - ieeexplore.ieee.org
This paper explores two methodologies for drowsiness detection using EEG signals in a
sustained-attention driving task considering pre-event time windows, and focusing on cross …

Changes in electrical brain activity and cognitive functions following mild to moderate COVID-19: a one-year prospective study after acute infection

P Andrei Appelt, A Taciana Sisconetto… - Clinical EEG and …, 2022 - journals.sagepub.com
The coronavirus disease 2019 (COVID-19) can disrupt various brain functions. Over a one-
year period, we aimed to assess brain activity and cognitive function in 53 COVID-19 …

Mental fatigue detection using a wearable commodity device and machine learning

C Goumopoulos, N Potha - Journal of Ambient Intelligence and …, 2023 - Springer
Mental fatigue is a psychophysiological state that has an intense adverse effect on the
quality of life, undermining both the mental and the physical health. As a consequence …

Applying neural networks with time-frequency features for the detection of mental fatigue

I Zorzos, I Kakkos, ST Miloulis, A Anastasiou… - Applied Sciences, 2023 - mdpi.com
The detection of mental fatigue is an important issue in the nascent field of
neuroergonomics. Although machine learning approaches and especially deep learning …

Eeg-cognet: A deep learning framework for cognitive state assessment using eeg brain connectivity

N Panwar, V Pandey, PP Roy - Biomedical Signal Processing and Control, 2024 - Elsevier
The assessment of cognitive states such as workload, attention, and fatigue is crucial in
cognitive science and human performance fields due to its significant impact on work …

EEG-based cross-subject mental fatigue recognition

Y Liu, Z Lan, J Cui, O Sourina… - … on cyberworlds (cw), 2019 - ieeexplore.ieee.org
Mental fatigue is common at work places, and it can lead to decreased attention, vigilance
and cognitive performance, which is dangerous in the situations such as driving, vessel …

Subject-Wise Cognitive Load Detection Using Time–Frequency EEG and Bi-LSTM

J Yedukondalu, D Sharma, LD Sharma - Arabian Journal for Science and …, 2024 - Springer
Cognitive load detection using electroencephalogram (EEG) signals is a technique
employed to understand and measure the mental workload or cognitive demands placed on …

Interweaving artificial intelligence and bio-signals in mental fatigue: unveiling dynamics and future pathways

S Parveen, MBB Heyat, F Akhtar… - … on Wavelet Active …, 2023 - ieeexplore.ieee.org
This study conducts a thorough examination of machine learning models within Artificial
Intelligence (AI)-integrated mental fatigue research, focusing on their identification and …