In the previous decade, breakthroughs in the central nervous system bioinformatics and
computational innovation have prompted significant developments in brain–computer …

Electroencephalogram (EEG) decoding aims to identify the perceptual, semantic, and
cognitive content of neural processing based on noninvasively measured brain activity …

The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …

Motor imagery electroencephalograph (MI-EEG) decoding plays a crucial role in develo**
motor imagery brain-computer interfaces (MI-BCIs). However, MI-EEG signals exhibit …

This literature review explores the pivotal role of brain–computer interface (BCI) technology,
coupled with electroencephalogram (EEG) technology, in advancing rehabilitation for …

Motor imagery (MI) electroencephalography (EEG) classification is an important part of the
brain-computer interface (BCI), allowing people with mobility problems to communicate with …

Abstract Electroencephalogram (EEG)-based Brain–Computer Interfaces (BCIs) build a
communication path between human brain and external devices. Among EEG-based BCI …

In this study, we introduce an innovative EEG signal reconstruction sub-module designed to
enhance the performance of deep learning models on EEG eye-tracking tasks. This sub …

Studies have investigated electroencephalogram (EEG)-based emotion recognition using
hand-crafted EEG features (eg, differential entropy) or the annotated emotion categories …

This article presents a new aviation brain-computer interface, which includes the
construction of a color brain power map and a cognitive detection network. The developed …