Objective. To develop and implement a novel approach which combines the technique of
scout EEG source imaging (ESI) with convolutional neural network (CNN) for the …

With the development of technology and the rise of the meta-universe concept, the brain-
computer interface (BCI) has become a hotspot in the research field, and the BCI based on …

Advancements in neuroscience and artificial intelligence are propelling rapid progress in
brain–computer interfaces (BCIs). These developments hold significant potential for …

Objective. When designing multiclass motor imagery-based brain–computer interface (MI-
BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of …

In this paper, we propose a novel transformer-based classification algorithm for the brain
computer interface (BCI) using a motor imagery (MI) electroencephalogram (EEG) signal. To …

Motor imagery (MI) is an important brain-computer interface (BCI) paradigm. The traditional
MI paradigm (imagining different limbs) limits the intuitive control of the outer devices, while …

Quaternions can be used as an alternative to model the fundamental patterns of
electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new …

We present an improvement to the quaternion‐based signal analysis (QSA) technique to
extract electroencephalography (EEG) signal features with a view to developing real‐time …

The main idea of brain-computer interfaces (BCIs) is to facilitate the lives of patients having
difficulties to move their muscles due to a disorder of their motor nervous systems but …

The purpose of a brain—computer interface (BCI) is the recording of brain signals to
translate them into commands. This work proposes new naturalistic and intuitive motor …