A review of EEG signal features and their application in driver drowsiness detection systems
Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …
is often approached using neurophysiological signals as the basis for building a reliable …
Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue
X Hu, G Lodewijks - Journal of safety research, 2020 - Elsevier
Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the
operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role …
operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role …
CNN and LSTM based ensemble learning for human emotion recognition using EEG recordings
A Iyer, SS Das, R Teotia, S Maheshwari… - Multimedia Tools and …, 2023 - Springer
Emotion is a significant parameter in daily life and is considered an important factor for
human interactions. The human-machine interactions and their advanced stages like …
human interactions. The human-machine interactions and their advanced stages like …
Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks
To investigate critical frequency bands and channels, this paper introduces deep belief
networks (DBNs) to constructing EEG-based emotion recognition models for three emotions …
networks (DBNs) to constructing EEG-based emotion recognition models for three emotions …
Hierarchical convolutional neural networks for EEG-based emotion recognition
Traditional machine learning methods suffer from severe overfitting in EEG-based emotion
reading. In this paper, we use hierarchical convolutional neural network (HCNN) to classify …
reading. In this paper, we use hierarchical convolutional neural network (HCNN) to classify …
Learning spatial–spectral–temporal EEG features with recurrent 3D convolutional neural networks for cross-task mental workload assessment
Mental workload assessment is essential for maintaining human health and preventing
accidents. Most research on this issue is limited to a single task. However, cross-task …
accidents. Most research on this issue is limited to a single task. However, cross-task …
Monitoring pilot's mental workload using ERPs and spectral power with a six-dry-electrode EEG system in real flight conditions
Recent technological progress has allowed the development of low-cost and highly portable
brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the …
brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the …
[HTML][HTML] Military applications of soldier physiological monitoring
KE Friedl - Journal of science and medicine in sport, 2018 - Elsevier
Wearable physiological status monitoring is part of modern precision medicine that permits
predictions about an individual's health and performance from their real-time physiological …
predictions about an individual's health and performance from their real-time physiological …
Applications of EEG indices for the quantification of human cognitive performance: A systematic review and bibliometric analysis
LE Ismail, W Karwowski - Plos one, 2020 - journals.plos.org
Background Neuroergonomics combines neuroscience with ergonomics to study human
performance using recorded brain signals. Such neural signatures of performance can be …
performance using recorded brain signals. Such neural signatures of performance can be …
[HTML][HTML] Aviation and neurophysiology: A systematic review
This paper systematically reviews 20 years of publications (N= 54) on aviation and
neurophysiology. The main goal is to provide an account of neurophysiological changes …
neurophysiology. The main goal is to provide an account of neurophysiological changes …