EEG-based brain-computer interfaces using motor-imagery: Techniques and challenges
Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
A comprehensive review on critical issues and possible solutions of motor imagery based electroencephalography brain-computer interface
Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of
communication through the utilization of neural activity generated due to kinesthetic …
communication through the utilization of neural activity generated due to kinesthetic …
Integrating EEG and MEG signals to improve motor imagery classification in brain–computer interface
MC Corsi, M Chavez, D Schwartz… - … journal of neural …, 2019 - World Scientific
We adopted a fusion approach that combines features from simultaneously recorded
electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve …
electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve …
How to successfully classify EEG in motor imagery BCI: a metrological analysis of the state of the art
Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
A systematic review on motor-imagery brain-connectivity-based computer interfaces
This review article discusses the definition and implementation of brain–computer interface
(BCI) system relying on brain connectivity (BC) and machine learning/deep learning (DL) for …
(BCI) system relying on brain connectivity (BC) and machine learning/deep learning (DL) for …
Evidence of variabilities in EEG dynamics during motor imagery-based multiclass brain–computer interface
Inter-subject and inter-session variabilities pose a significant challenge in
electroencephalogram (EEG)-based brain-computer interface (BCI) systems. Furthermore …
electroencephalogram (EEG)-based brain-computer interface (BCI) systems. Furthermore …
An automatic subject specific channel selection method for enhancing motor imagery classification in EEG-BCI using correlation
A motor imagery (MI) based brain–computer interface (BCI) decodes the motor intention
from the electroencephalogram (EEG) of a subject and translates this into a control signal …
from the electroencephalogram (EEG) of a subject and translates this into a control signal …
Comparative analysis of features extracted from EEG spatial, spectral and temporal domains for binary and multiclass motor imagery classification
The electroencephalogram (EEG) remains the predominant source of neurophysiological
signals for motor imagery-based brain-computer interfaces (MI-BCIs). Various features can …
signals for motor imagery-based brain-computer interfaces (MI-BCIs). Various features can …
Electroencephalographic motor imagery brain connectivity analysis for BCI: a review
M Hamedi, SH Salleh, AM Noor - Neural computation, 2016 - ieeexplore.ieee.org
Recent research has reached a consensus on the feasibility of motor imagery brain-
computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most …
computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most …
EEG-based BCIs on motor imagery paradigm using wearable technologies: a systematic review
In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …