Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

AE Hramov, VA Maksimenko, AN Pisarchik - Physics Reports, 2021 - Elsevier
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

EEG-based brain-computer interfaces (BCIs): A survey of recent studies on signal sensing technologies and computational intelligence approaches and their …

X Gu, Z Cao, A Jolfaei, P Xu, D Wu… - … /ACM transactions on …, 2021 - ieeexplore.ieee.org
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact
with the environment. Recent advancements in technology and machine learning algorithms …

Complex networks and deep learning for EEG signal analysis

Z Gao, W Dang, X Wang, X Hong, L Hou, K Ma… - Cognitive …, 2021 - Springer
Electroencephalogram (EEG) signals acquired from brain can provide an effective
representation of the human's physiological and pathological states. Up to now, much work …

Subject-independent brain–computer interfaces based on deep convolutional neural networks

OY Kwon, MH Lee, C Guan… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
For a brain-computer interface (BCI) system, a calibration procedure is required for each
individual user before he/she can use the BCI. This procedure requires approximately 20-30 …

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 …

EEG-ConvTransformer for single-trial EEG-based visual stimulus classification

S Bagchi, DR Bathula - Pattern Recognition, 2022 - Elsevier
Different categories of visual stimuli evoke distinct activation patterns in the human brain.
These patterns can be captured with EEG for utilization in application such as Brain …

BrainPrint: EEG biometric identification based on analyzing brain connectivity graphs

M Wang, J Hu, HA Abbass - Pattern Recognition, 2020 - Elsevier
Research on brain biometrics using electroencephalographic (EEG) signals has received
increasing attentions in recent years. In particular, it has been recognized that the brain …

A novel classification framework using the graph representations of electroencephalogram for motor imagery based brain-computer interface

J **, H Sun, I Daly, S Li, C Liu, X Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The motor imagery (MI) based brain-computer interfaces (BCIs) have been proposed as a
potential physical rehabilitation technology. However, the low classification accuracy …

Evolving signal processing for brain–computer interfaces

S Makeig, C Kothe, T Mullen… - Proceedings of the …, 2012 - ieeexplore.ieee.org
Because of the increasing portability and wearability of noninvasive electrophysiological
systems that record and process electrical signals from the human brain, automated systems …

Functional networks of the brain: from connectivity restoration to dynamic integration

AE Hramov, NS Frolov, VA Maksimenko… - Physics …, 2021 - iopscience.iop.org
A review of physical and mathematical methods for reconstructing the functional networks of
the brain based on recorded brain activity is presented. Various methods are considered, as …