Review of machine learning techniques for EEG based brain computer interface

S Aggarwal, N Chugh - Archives of Computational Methods in …, 2022 - Springer
A brain computer interface (BCI) framework uses computer algorithms to detect mental
activity patterns and manipulate external devices. Because of its simplicity and non …

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 …

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 …

A comprehensive review of EEG-based brain–computer interface paradigms

R Abiri, S Borhani, EW Sellers, Y Jiang… - Journal of neural …, 2019 - iopscience.iop.org
Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …

Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system

J Kevric, A Subasi - Biomedical Signal Processing and Control, 2017 - Elsevier
In this study, three popular signal processing techniques (Empirical Mode Decomposition,
Discrete Wavelet Transform, and Wavelet Packet Decomposition) were investigated for the …

fNIRS-based brain-computer interfaces: a review

N Naseer, KS Hong - Frontiers in human neuroscience, 2015 - frontiersin.org
A brain-computer interface (BCI) is a communication system that allows the use of brain
activity to control computers or other external devices. It can, by bypassing the peripheral …

EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review

S Yasin, SA Hussain, S Aslan, I Raza… - Computer Methods and …, 2021 - Elsevier
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …

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 …

Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces

KS Hong, MJ Khan, MJ Hong - Frontiers in human neuroscience, 2018 - frontiersin.org
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …

[HTML][HTML] Hybrid brain–computer interface techniques for improved classification accuracy and increased number of commands: a review

KS Hong, MJ Khan - Frontiers in neurorobotics, 2017 - frontiersin.org
In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …