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 …

Coherence resonance in neural networks: Theory and experiments

AN Pisarchik, AE Hramov - Physics Reports, 2023‏ - Elsevier
The paper is devoted to the review of the coherence resonance phenomenon in excitable
neural networks. In particular, we explain how coherence can be measured and how noise …

Real-time EEG–EMG human–machine interface-based control system for a lower-limb exoskeleton

SY Gordleeva, SA Lobov, NA Grigorev… - Ieee …, 2020‏ - ieeexplore.ieee.org
This article presents a rehabilitation technique based on a lower-limb exoskeleton
integrated with a human–machine interface (HMI). HMI is used to record and process …

NeuroGrasp: Real-time EEG classification of high-level motor imagery tasks using a dual-stage deep learning framework

JH Cho, JH Jeong, SW Lee - IEEE Transactions on Cybernetics, 2021‏ - ieeexplore.ieee.org
Brain–computer interfaces (BCIs) have been widely employed to identify and estimate a
user's intention to trigger a robotic device by decoding motor imagery (MI) from an …

Electroencephalogram-based motor imagery brain–computer interface using multivariate iterative filtering and spatial filtering

K Das, RB Pachori - IEEE Transactions on Cognitive and …, 2022‏ - ieeexplore.ieee.org
In motor imagery (MI)-based brain–computer interface (BCI), common spatial pattern (CSP)
is most popularly used for discriminant feature extraction. However, the performance of CSP …

[HTML][HTML] EEG channel selection techniques in motor imagery applications: a review and new perspectives

Abdullah, I Faye, MR Islam - Bioengineering, 2022‏ - mdpi.com
Communication, neuro-prosthetics, and environmental control are just a few applications for
disabled persons who use robots and manipulators that use brain-computer interface (BCI) …

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 …

[PDF][PDF] Immersive innovations: exploring the diverse applications of virtual reality (VR) in healthcare

CK Javvaji, H Reddy, JD Vagha, A Taksande… - Cureus, 2024‏ - cureus.com
Virtual reality (VR) has experienced a remarkable evolution over recent decades, evolving
from its initial applications in specific military domains to becoming a ubiquitous and easily …

Brain-computer interface paradigms and neural coding

P Tai, P Ding, F Wang, A Gong, T Li, L Zhao… - Frontiers in …, 2024‏ - frontiersin.org
Brain signal patterns generated in the central nervous system of brain-computer interface
(BCI) users are closely related to BCI paradigms and neural coding. In BCI systems, BCI …

Brain–machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study

L Ferrero, P Soriano-Segura, J Navarro… - Journal of …, 2024‏ - Springer
Background This research focused on the development of a motor imagery (MI) based brain–
machine interface (BMI) using deep learning algorithms to control a lower-limb robotic …