Past, present, and future of EEG-based BCI applications

K Värbu, N Muhammad, Y Muhammad - Sensors, 2022 - mdpi.com
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …

Systematic review of driving simulator validation studies

RA Wynne, V Beanland, PM Salmon - Safety science, 2019 - Elsevier
Driving simulators are a common tool for researching driver behaviour, providing practical,
safe, and controlled environments. Despite their frequent use in research, there is relatively …

Toward open-world electroencephalogram decoding via deep learning: A comprehensive survey

X Chen, C Li, A Liu, MJ McKeown… - IEEE Signal …, 2022 - ieeexplore.ieee.org
Electroencephalogram (EEG) decoding aims to identify the perceptual, semantic, and
cognitive content of neural processing based on noninvasively measured brain activity …

The Berlin brain-computer interface: progress beyond communication and control

B Blankertz, L Acqualagna, S Dähne, S Haufe… - Frontiers in …, 2016 - frontiersin.org
The combined effect of fundamental results about neurocognitive processes and
advancements in decoding mental states from ongoing brain signals has brought forth a …

Correcting robot mistakes in real time using EEG signals

AF Salazar-Gomez, J DelPreto, S Gil… - … on robotics and …, 2017 - ieeexplore.ieee.org
Communication with a robot using brain activity from a human collaborator could provide a
direct and fast feedback loop that is easy and natural for the human, thereby enabling a wide …

EEG-based mental workload neurometric to evaluate the impact of different traffic and road conditions in real driving settings

G Di Flumeri, G Borghini, P Aricò, N Sciaraffa… - Frontiers in human …, 2018 - frontiersin.org
Car driving is considered a very complex activity, consisting of different concomitant tasks
and subtasks, thus it is crucial to understand the impact of different factors, such as road …

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 …

Review of the state-of-the-art of brain-controlled vehicles

A Hekmatmanesh, PHJ Nardelli, H Handroos - IEEE Access, 2021 - ieeexplore.ieee.org
Brain-Controlled Vehicle (BCV) is an already established technology usually designed for
disabled patients. This review focuses on the most relevant topics on brain-controlled …

The sample size matters: to what extent the participant reduction affects the outcomes of a neuroscientific research. A case-study in neuromarketing field

A Vozzi, V Ronca, P Aricò, G Borghini, N Sciaraffa… - Sensors, 2021 - mdpi.com
The sample size is a crucial concern in scientific research and even more in behavioural
neurosciences, where besides the best practice it is not always possible to reach large …

Advanced Electrode Technologies for Noninvasive Brain–Computer Interfaces

S Lin, J Jiang, K Huang, L Li, X He, P Du, Y Wu, J Liu… - ACS …, 2023 - ACS Publications
Brain–computer interfaces (BCIs) have garnered significant attention in recent years due to
their potential applications in medical, assistive, and communication technologies. Building …