Motor imagery electroencephalography (EEG) decoding is an essential part of brain-
computer interfaces (BCIs) which help motor-disabled patients to communicate with the …

Recognition of motor imagery intention is one of the hot current research focuses of brain-
computer interface (BCI) studies. It can help patients with physical dyskinesia to convey their …

Speller brain-computer interface (BCI) systems can help neuromuscular disorders patients
write their thoughts by using the electroencephalogram (EEG) signals by just focusing on the …

Conventionally, event-related potential (ERP) analysis relies on the researcher to identify
the sensors and time points where an effect is expected. However, this approach is prone to …

Aiming at the complexity, nonlinearity and difficulty in modeling of nonlinear system. In this
paper, an improved back-propagation (BP) neural network based on restricted boltzmann …

Background and objective Despite the widespread prevalence of Multiple Sclerosis (MS),
the study of brain interactions is still poorly understood. Moreover, there has always been a …

Folk vocal music is an important part of music majors in colleges and universities (CaU), and
the core of music education is AE. Therefore, in vocal music teaching, students should be …

The article presents an original method for the automatic assessment of the quality of event-
related potentials (ERPs), based on the calculation of the coefficient ε, which describes the …

A new approach is introduced to address the subject dependency problem in P300-based
brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event …

A Bayesian deep restricted Boltzmann–Kohonen architecture for data clustering termed
deep restricted Boltzmann machine (DRBM)-ClustNet is proposed. This core-clustering …