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 …

[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 …

EEG dataset and OpenBMI toolbox for three BCI paradigms: An investigation into BCI illiteracy

MH Lee, OY Kwon, YJ Kim, HK Kim, YE Lee… - …, 2019 - academic.oup.com
Background Electroencephalography (EEG)-based brain-computer interface (BCI) systems
are mainly divided into three major paradigms: motor imagery (MI), event-related potential …

High-speed spelling with a noninvasive brain–computer interface

X Chen, Y Wang, M Nakanishi, X Gao… - Proceedings of the …, 2015 - National Acad Sciences
The past 20 years have witnessed unprecedented progress in brain–computer interfaces
(BCIs). However, low communication rates remain key obstacles to BCI-based …

Robust similarity measurement based on a novel time filter for SSVEPs detection

J Jin, Z Wang, R Xu, C Liu, X Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has
received extensive attention in research for the less training time, excellent recognition …

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface

X Chen, Y Wang, S Gao, TP Jung… - Journal of neural …, 2015 - iopscience.iop.org
Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-
state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) due to its …

A convolutional neural network for steady state visual evoked potential classification under ambulatory environment

NS Kwak, KR Müller, SW Lee - PloS one, 2017 - journals.plos.org
The robust analysis of neural signals is a challenging problem. Here, we contribute a
convolutional neural network (CNN) for the robust classification of a steady-state visual …

Visual and auditory brain–computer interfaces

S Gao, Y Wang, X Gao, B Hong - IEEE transactions on …, 2014 - ieeexplore.ieee.org
Over the past several decades, electroencephalogram (EEG)-based brain-computer
interfaces (BCIs) have attracted attention from researchers in the field of neuroscience …

Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general

TO Zander, C Kothe - Journal of neural engineering, 2011 - iopscience.iop.org
Cognitive monitoring is an approach utilizing realtime brain signal decoding (RBSD) for
gaining information on the ongoing cognitive user state. In recent decades this approach …

Steady-state visually evoked potentials: focus on essential paradigms and future perspectives

FB Vialatte, M Maurice, J Dauwels, A Cichocki - Progress in neurobiology, 2010 - Elsevier
After 40 years of investigation, steady-state visually evoked potentials (SSVEPs) have been
shown to be useful for many paradigms in cognitive (visual attention, binocular rivalry …