EEG-based brain-computer interfaces: a thorough literature survey

HJ Hwang, S Kim, S Choi, CH Im - International Journal of Human …, 2013 - Taylor & Francis
Brain–computer interface (BCI) technology has been studied with the fundamental goal of
hel** disabled people communicate with the outside world using brain signals. In …

Non-invasive brain-computer interfaces: state of the art and trends

BJ Edelman, S Zhang, G Schalk… - IEEE Reviews in …, 2024 - ieeexplore.ieee.org
Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to
widely influence research, clinical and recreational use. Non-invasive BCI approaches are …

A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control

Y Li, J Pan, F Wang, Z Yu - IEEE Transactions on Biomedical …, 2013 - ieeexplore.ieee.org
In this paper, a hybrid brain-computer interface (BCI) system combining P300 and steady-
state visual evoked potential (SSVEP) is proposed to improve the performance of …

Enhanced low-latency detection of motor intention from EEG for closed-loop brain-computer interface applications

R Xu, N Jiang, C Lin… - IEEE Transactions …, 2013 - ieeexplore.ieee.org
In recent years, the detection of voluntary motor intentions from electroencephalogram
(EEG) has been used for triggering external devices in closed-loop brain–computer interface …

Self-paced operation of an SSVEP-Based orthosis with and without an imagery-based “brain switch:” a feasibility study towards a hybrid BCI

G Pfurtscheller, T Solis-Escalante… - IEEE transactions on …, 2010 - ieeexplore.ieee.org
This work introduces a hybrid brain-computer interface (BCI) composed of an imagery-
based brain switch and a steady-state visual evoked potential (SSVEP)-based BCI. The …

Detection of movement intention from single-trial movement-related cortical potentials

IK Niazi, N Jiang, O Tiberghien… - Journal of neural …, 2011 - iopscience.iop.org
Detection of movement intention from neural signals combined with assistive technologies
may be used for effective neurofeedback in rehabilitation. In order to promote plasticity, a …

[HTML][HTML] EEG neural correlates of goal-directed movement intention

J Pereira, P Ofner, A Schwarz, AI Sburlea… - Neuroimage, 2017 - Elsevier
Using low-frequency time-domain electroencephalographic (EEG) signals we show, for the
same type of upper limb movement, that goal-directed movements have different neural …

A brain-machine interface based on ERD/ERS for an upper-limb exoskeleton control

Z Tang, S Sun, S Zhang, Y Chen, C Li, S Chen - Sensors, 2016 - mdpi.com
To recognize the user's motion intention, brain-machine interfaces (BMI) usually decode
movements from cortical activity to control exoskeletons and neuroprostheses for daily …

EEG-based classification of imaginary left and right foot movements using beta rebound

Y Hashimoto, J Ushiba - Clinical neurophysiology, 2013 - Elsevier
Objective The purpose of this study was to investigate cortical lateralization of event-related
(de) synchronization during left and right foot motor imagery tasks and to determine …

Development of a low-cost EEG-controlled hand exoskeleton 3D printed on textiles

RS Araujo, CR Silva, SPN Netto, E Morya… - Frontiers in …, 2021 - frontiersin.org
Stroke survivors can be affected by motor deficits in the hand. Robotic equipment associated
with brain–machine interfaces (BMI) may aid the motor rehabilitation of these patients. BMIs …