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 …
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 …
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 …
Motor execution reduces EEG signals complexity: Recurrence quantification analysis study
The development of new approaches to detect motor-related brain activity is key in many
aspects of science, especially in brain–computer interface applications. Even though some …
aspects of science, especially in brain–computer interface applications. Even though some …
Event-related coherence in visual cortex and brain noise: An meg study
The analysis of neurophysiological data using the two most widely used open-source
MATLAB toolboxes, FieldTrip and Brainstorm, validates our hypothesis about the correlation …
MATLAB toolboxes, FieldTrip and Brainstorm, validates our hypothesis about the correlation …
The oxygen saturation in the primary motor cortex during a single hand movement: functional near-infrared spectroscopy (fnirs) study
Functional near-infrared spectroscopy is a noninvasive optical imaging technique to register
brain activity. It utilizes near-infrared light to evaluate the oxygenated (HbO) and …
brain activity. It utilizes near-infrared light to evaluate the oxygenated (HbO) and …
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) …