Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review

EH Houssein, A Hammad, AA Ali - Neural Computing and Applications, 2022 - Springer
Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …

Current status, challenges, and possible solutions of EEG-based brain-computer interface: a comprehensive review

M Rashid, N Sulaiman, A PP Abdul Majeed… - Frontiers in …, 2020 - frontiersin.org
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …

Brain computer interface based applications for training and rehabilitation of students with neurodevelopmental disorders. A literature review

G Papanastasiou, A Drigas, C Skianis, M Lytras - Heliyon, 2020 - cell.com
The aim of this article is to explore a paradigm shift on Brain Computer Interface (BCI)
research, as well as on intervention best practices for training and rehabilitation of students …

Brain computer interface: control signals review

RA Ramadan, AV Vasilakos - Neurocomputing, 2017 - Elsevier
Abstract Brain Computer Interface (BCI) is defined as a combination of hardware and
software that allows brain activities to control external devices or even computers. The …

A review on Virtual Reality and Augmented Reality use-cases of Brain Computer Interface based applications for smart cities

V Kohli, U Tripathi, V Chamola, BK Rout… - Microprocessors and …, 2022 - Elsevier
Abstract Brain Computer Interfaces (BCIs) and Extended Reality (XR) have seen significant
advances as independent disciplines over the past 50 years. XR has been developed as an …

EEG-Based Brain–Computer Interfaces for Communication and Rehabilitation of People with Motor Impairment: A Novel Approach of the 21st Century

I Lazarou, S Nikolopoulos, PC Petrantonakis… - Frontiers in human …, 2018 - frontiersin.org
People with severe neurological impairments face many challenges in sensorimotor
functions and communication with the environment; therefore they have increased demand …

A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers

X Zhang, L Yao, X Wang, J Monaghan… - Journal of neural …, 2021 - iopscience.iop.org
Brain signals refer to the biometric information collected from the human brain. The research
on brain signals aims to discover the underlying neurological or physical status of the …

Decoding covert speech from EEG-a comprehensive review

JT Panachakel, AG Ramakrishnan - Frontiers in Neuroscience, 2021 - frontiersin.org
Over the past decade, many researchers have come up with different implementations of
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …

Deep learning for EEG-based preference classification in neuromarketing

M Aldayel, M Ykhlef, A Al-Nafjan - Applied Sciences, 2020 - mdpi.com
Featured Application This article presents an application of deep learning in preference
detection performed using EEG-based BCI. Abstract The traditional marketing …

[PDF][PDF] A survey on deep learning based brain computer interface: Recent advances and new frontiers

X Zhang, L Yao, X Wang, J Monaghan… - arXiv preprint arXiv …, 2019 - researchgate.net
Brain-Computer Interface (BCI) bridges human's neural world and the outer physical world
by decoding individuals' brain signals into commands recognizable by computer devices …