Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review
The brain–computer interface (BCI) is an emerging technology that has the potential to
revolutionize the world, with numerous applications ranging from healthcare to human …
revolutionize the world, with numerous applications ranging from healthcare to human …
A review on transfer learning in EEG signal analysis
Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
interaction and neurological disease diagnosis, requires a large amount of labeled data for …
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 …
Riemannian flow matching on general geometries
We propose Riemannian Flow Matching (RFM), a simple yet powerful framework for training
continuous normalizing flows on manifolds. Existing methods for generative modeling on …
continuous normalizing flows on manifolds. Existing methods for generative modeling on …
Spatio-spectral feature representation for motor imagery classification using convolutional neural networks
Convolutional neural networks (CNNs) have recently been applied to electroencephalogram
(EEG)-based brain–computer interfaces (BCIs). EEG is a noninvasive neuroimaging …
(EEG)-based brain–computer interfaces (BCIs). EEG is a noninvasive neuroimaging …
Transfer learning in brain-computer interfaces
The performance of brain-computer interfaces (BCIs) improves with the amount of available
training data; the statistical distribution of this data, however, varies across subjects as well …
training data; the statistical distribution of this data, however, varies across subjects as well …