EEG-based brain-computer interfaces using motor-imagery: Techniques and challenges
Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Application of artificial intelligence techniques for brain-computer interface in mental fatigue detection: a systematic review (2011-2022)
Mental fatigue is a psychophysical condition with a significant adverse effect on daily life,
compromising both physical and mental wellness. We are experiencing challenges in this …
compromising both physical and mental wellness. We are experiencing challenges in this …
A systematic survey of driving fatigue monitoring
The appearance of fatigue is not conducive to driving activities because this state can affect
driving performance and even cause life-threatening consequences. To reduce various …
driving performance and even cause life-threatening consequences. To reduce various …
EEG-based neural networks approaches for fatigue and drowsiness detection: A survey
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 …
correlated with a progressive decline in response time, compromised processing of …
A survey and tutorial of EEG-based brain monitoring for driver state analysis
C Zhang, A Eskandarian - arXiv preprint arXiv:2008.11226, 2020 - arxiv.org
Drivers cognitive and physiological states affect their ability to control their vehicles. Thus,
these driver states are important to the safety of automobiles. The design of advanced driver …
these driver states are important to the safety of automobiles. The design of advanced driver …
VR motion sickness recognition by using EEG rhythm energy ratio based on wavelet packet transform
X Li, C Zhu, C Xu, J Zhu, Y Li, S Wu - Computer methods and programs in …, 2020 - Elsevier
Background and objectives Virtual reality motion sickness (VRMS) is one of the main factors
hindering the development of VR technology. At present, the VRMS recognition methods …
hindering the development of VR technology. At present, the VRMS recognition methods …
Synchronization and identification of nonlinear systems by using a novel self-evolving interval type-2 fuzzy LSTM-neural network
H Wang, C Luo, X Wang - Engineering Applications of Artificial Intelligence, 2019 - Elsevier
Nonlinear systems widely exist in the real world. Researches on the synchronization and
identification of nonlinear systems have both theoretical and practical interests. However …
identification of nonlinear systems have both theoretical and practical interests. However …
Drivers fatigue level prediction using facial, and head behavior information
HA Kassem, M Chowdhury, JH Abawajy - IEEE Access, 2021 - ieeexplore.ieee.org
With driver fatigue continues to cause serious and deadly car and motorcycles accidents, the
need for automatically recognizing driver fatigue and alerting the drivers is apparent …
need for automatically recognizing driver fatigue and alerting the drivers is apparent …
Cognition-driven traffic simulation for unstructured road networks
H Wang, XY He, LY Chen, JR Yin, L Han… - Journal of Computer …, 2020 - Springer
Dynamic changes of traffic features in unstructured road networks challenge the scene-
cognitive abilities of drivers, which brings various heterogeneous traffic behaviors. Modeling …
cognitive abilities of drivers, which brings various heterogeneous traffic behaviors. Modeling …