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 …
Sparse Bayesian classification of EEG for brain–computer interface
Regularization has been one of the most popular approaches to prevent overfitting in
electroencephalogram (EEG) classification of brain-computer interfaces (BCIs). The …
electroencephalogram (EEG) classification of brain-computer interfaces (BCIs). The …
Differentiation of schizophrenia by combining the spatial EEG brain network patterns of rest and task P300
The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …
The dynamic brain networks of motor imagery: time-varying causality analysis of scalp EEG
Motor imagery (MI) requires subjects to visualize the requested motor behaviors, which
involves a large-scale network that spans multiple brain areas. The corresponding cortical …
involves a large-scale network that spans multiple brain areas. The corresponding cortical …
Multiple frequencies sequential coding for SSVEP-based brain-computer interface
Background Steady-state visual evoked potential (SSVEP)-based brain-computer interface
(BCI) has become one of the most promising modalities for a practical noninvasive BCI …
(BCI) has become one of the most promising modalities for a practical noninvasive BCI …
Structural and functional correlates of motor imagery BCI performance: Insights from the patterns of fronto-parietal attention network
Motor imagery (MI)-based brain-computer interfaces (BCIs) have been widely used for
rehabilitation of motor abilities and prosthesis control for patients with motor impairments …
rehabilitation of motor abilities and prosthesis control for patients with motor impairments …
The hybrid BCI system for movement control by combining motor imagery and moving onset visual evoked potential
T Ma, H Li, L Deng, H Yang, X Lv, P Li… - Journal of neural …, 2017 - iopscience.iop.org
Objective. Movement control is an important application for EEG-BCI (EEG-based brain–
computer interface) systems. A single-modality BCI cannot provide an efficient and natural …
computer interface) systems. A single-modality BCI cannot provide an efficient and natural …
[HTML][HTML] Predicting individual decision-making responses based on single-trial EEG
Decision-making plays an essential role in the interpersonal interactions and cognitive
processing of individuals. There has been increasing interest in being able to predict an …
processing of individuals. There has been increasing interest in being able to predict an …
Facial expressions classification and false label reduction using LDA and threefold SVM
Abstract Representation and classification of multi-dimensional data are current key
research areas. The representation of data in two classes is more feasible than multi-class …
research areas. The representation of data in two classes is more feasible than multi-class …
EEG based emotion recognition by hierarchical bayesian spectral regression framework
L Yang, Q Tang, Z Chen, S Zhang, Y Mu, Y Yan… - Journal of Neuroscience …, 2024 - Elsevier
Spectral regression (SR), a graph-based learning regression model, can be used to extract
features from graphs to realize efficient dimensionality reduction. However, due to the SR …
features from graphs to realize efficient dimensionality reduction. However, due to the SR …