Brain computer interfaces (BCI) provide a direct communication link between the brain and a
computer or other external devices. They offer an extended degree of freedom either by …

Brain-computer interfaces (BCIs) have achieved significant success in controlling external
devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor …

Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …

Motor Imagery Brain-Computer Interfaces (MI-BCIs) are AI-driven systems that capture brain
activity patterns associated with mental imagination of movement and convert them into …

Following the research question and the relevant dataset, feature extraction is the most
important component of machine learning and data science pipelines. The wavelet …

The translation of brain dynamics into natural language is pivotal for brain-computer
interfaces (BCIs), a field that has seen substantial growth in recent years. With the swift …

In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI)
based Brain Computer Interfaces (BCIs) called EEGSym. Our implementation aims to …

State-of-the-art brain-to-text systems have achieved great success in decoding language
directly from brain signals using neural networks. However, current approaches are limited …

Electroencephalographic measurement of cortical activity subserving motor behavior varies
among different individuals, restricting the potential of brain computer interfaces (BCIs) …

Inter-subject transfer learning is a long-standing problem in brain-computer interfaces (BCIs)
and has not yet been fully realized due to high inter-subject variability in the brain signals …