[HTML][HTML] Wireless EEG: A survey of systems and studies

G Niso, E Romero, JT Moreau, A Araujo, LR Krol - NeuroImage, 2023 - Elsevier
The popular brain monitoring method of electroencephalography (EEG) has seen a surge in
commercial attention in recent years, focusing mostly on hardware miniaturization. This has …

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 …

In-ear integrated sensor array for the continuous monitoring of brain activity and of lactate in sweat

Y Xu, E De la Paz, A Paul, K Mahato… - Nature Biomedical …, 2023 - nature.com
Owing to the proximity of the ear canal to the central nervous system, in-ear
electrophysiological systems can be used to unobtrusively monitor brain states. Here, by …

Three-dimensional integrated stretchable electronics

Z Huang, Y Hao, Y Li, H Hu, C Wang, A Nomoto… - Nature …, 2018 - nature.com
Stretchable electronics is an emerging technology that creates devices with the ability to
conform to nonplanar and dynamic surfaces such as the human body. Current stretchable …

Brain–computer interface spellers: A review

A Rezeika, M Benda, P Stawicki, F Gembler, A Saboor… - Brain sciences, 2018 - mdpi.com
A Brain–Computer Interface (BCI) provides a novel non-muscular communication method
via brain signals. A BCI-speller can be considered as one of the first published BCI …

Multi-kernel extreme learning machine for EEG classification in brain-computer interfaces

Y Zhang, Y Wang, G Zhou, J **, B Wang… - Expert Systems with …, 2018 - Elsevier
One of the most important issues for the development of a motor-imagery based brain-
computer interface (BCI) is how to design a powerful classifier with strong generalization …

[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 …

Hybrid EEG–fNIRS-based eight-command decoding for BCI: application to quadcopter control

MJ Khan, KS Hong - Frontiers in neurorobotics, 2017 - frontiersin.org
In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …

Sparse group representation model for motor imagery EEG classification

Y Jiao, Y Zhang, X Chen, E Yin, J **… - IEEE journal of …, 2018 - ieeexplore.ieee.org
A potential limitation of a motor imagery (MI) based brain-computer interface (BCI) is that it
usually requires a relatively long time to record sufficient electroencephalogram (EEG) data …

[HTML][HTML] A hybrid steady-state visual evoked response-based brain-computer interface with MEG and EEG

X Li, J Chen, N Shi, C Yang, P Gao, X Chen… - Expert Systems with …, 2023 - Elsevier
While recent developments in electroencephalogram (EEG)-based brain-computer
interfaces (BCIs) have enabled a bridge between the brain and external devices with …