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Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
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 …
review the physical principles of BCIs, and underlying novel approaches for registration …
Coherence resonance in neural networks: Theory and experiments
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 …
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
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 …
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
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 …
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
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 …
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
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) …
disabled persons who use robots and manipulators that use brain-computer interface (BCI) …
Functional networks of the brain: from connectivity restoration to dynamic integration
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 …
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 …
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 …
(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 …
machine interface (BMI) using deep learning algorithms to control a lower-limb robotic …