Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness

G Borghini, L Astolfi, G Vecchiato, D Mattia… - … & Biobehavioral Reviews, 2014‏ - Elsevier
This paper reviews published papers related to neurophysiological measurements (
electroencephalography: EEG, electrooculography EOG; heart rate: HR) in pilots/drivers …

Artifact removal in physiological signals—Practices and possibilities

KT Sweeney, TE Ward… - IEEE transactions on …, 2012‏ - ieeexplore.ieee.org
The combination of reducing birth rate and increasing life expectancy continues to drive the
demographic shift toward an aging population. This, in turn, places an ever-increasing …

Regional brain wave activity changes associated with fatigue

A Craig, Y Tran, N Wijesuriya, H Nguyen - Psychophysiology, 2012‏ - Wiley Online Library
Assessing brain wave activity is a viable strategy for monitoring fatigue when performing
tasks such as driving, and numerous studies have been conducted in this area. However …

EEG signal analysis for the assessment and quantification of driver's fatigue

S Kar, M Bhagat, A Routray - … research part F: traffic psychology and …, 2010‏ - Elsevier
Fatigue in human drivers is a serious cause of road accidents. Hence, it is important to
devise methods to detect and quantify the fatigue. This paper presents a method based on a …

End-to-end fatigue driving EEG signal detection model based on improved temporal-graph convolution network

H Jia, Z **ao, P Ji - Computers in Biology and Medicine, 2023‏ - Elsevier
Fatigue driving is one of the leading causes of traffic accidents, so fatigue driving detection
technology plays a crucial role in road safety. The physiological information-based fatigue …

Using Muse: Rapid mobile assessment of brain performance

OE Krigolson, MR Hammerstrom, W Abimbola… - Frontiers in …, 2021‏ - frontiersin.org
The advent of mobile electroencephalography (mEEG) has created a means for large scale
collection of neural data thus affording a deeper insight into cognitive phenomena such as …

EEG-based drowsiness detection for safe driving using chaotic features and statistical tests

Z Mardi, SNM Ashtiani, M Mikaili - Journal of Medical Signals & …, 2011‏ - journals.lww.com
Electro encephalography (EEG) is one of the most reliable sources to detect sleep onset
while driving. In this study, we have tried to demonstrate that sleepiness and alertness …

[HTML][HTML] Real-time ECG-based detection of fatigue driving using sample entropy

F Wang, H Wang, R Fu - Entropy, 2018‏ - mdpi.com
In present work, the heart rate variability (HRV) characteristics, calculated by sample entropy
(SampEn), were used to analyze the driving fatigue state at successive driving stages …

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network

S Mahmud, MS Hossain, MEH Chowdhury… - Neural Computing and …, 2023‏ - Springer
Electroencephalogram (EEG) signals suffer substantially from motion artifacts when
recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many …

An EEG-based attention recognition method: fusion of time domain, frequency domain, and non-linear dynamics features

D Chen, H Huang, X Bao, J Pan, Y Li - Frontiers in neuroscience, 2023‏ - frontiersin.org
Introduction Attention is a complex cognitive function of human brain that plays a vital role in
our daily lives. Electroencephalogram (EEG) is used to measure and analyze attention due …