Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
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 …
Driver behavior detection and classification using deep convolutional neural networks
Driver behavior monitoring system as Intelligent Transportation Systems (ITS) have been
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces
VJ Lawhern, AJ Solon, NR Waytowich… - Journal of neural …, 2018 - iopscience.iop.org
Objective. Brain–computer interfaces (BCI) enable direct communication with a computer,
using neural activity as the control signal. This neural signal is generally chosen from a …
using neural activity as the control signal. This neural signal is generally chosen from a …
A review of psychophysiological measures to assess cognitive states in real-world driving
As driving functions become increasingly automated, motorists run the risk of becoming
cognitively removed from the driving process. Psychophysiological measures may provide …
cognitively removed from the driving process. Psychophysiological measures may provide …
A comprehensive survey of driving monitoring and assistance systems
MQ Khan, S Lee - Sensors, 2019 - mdpi.com
Improving a vehicle driver's performance decreases the damage caused by, and chances of,
road accidents. In recent decades, engineers and researchers have proposed several …
road accidents. In recent decades, engineers and researchers have proposed several …
Driver behavior analysis for safe driving: A survey
S Kaplan, MA Guvensan, AG Yavuz… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Driver drowsiness and distraction are two main reasons for traffic accidents and the related
financial losses. Therefore, researchers have been working for more than a decade on …
financial losses. Therefore, researchers have been working for more than a decade on …
EEG-based cross-subject driver drowsiness recognition with an interpretable convolutional neural network
In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still
challenging to design a calibration-free system, since EEG signals vary significantly among …
challenging to design a calibration-free system, since EEG signals vary significantly among …
A hybrid approach to detect driver drowsiness utilizing physiological signals to improve system performance and wearability
Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has
become an area of substantial research attention in recent years. The present study …
become an area of substantial research attention in recent years. The present study …
Driver inattention monitoring system for intelligent vehicles: A review
Y Dong, Z Hu, K Uchimura… - IEEE transactions on …, 2010 - ieeexplore.ieee.org
In this paper, we review the state-of-the-art technologies for driver inattention monitoring,
which can be classified into the following two main categories: 1) distraction and 2) fatigue …
which can be classified into the following two main categories: 1) distraction and 2) fatigue …