Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …

Electroencephalogram (EEG) plays an important role in identifying brain activity and
behavior. However, the recorded electrical activity always be contaminated with artifacts and …

The electroencephalography (EEG) signal is a noninvasive and complex signal that has
numerous applications in biomedical fields, including sleep and the brain–computer …

This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …

Objective. Deep learning (DL) networks are increasingly attracting attention across various
fields, including electroencephalography (EEG) signal processing. These models provide …

Standard artifact removal methods for electroencephalographic (EEG) signals are either
based on Independent Component Analysis (ICA) or they regress out ocular activity …

A brain-computer interface (BCI) is a hardware and software communications system that
permits cerebral activity alone to control computers or external devices. The immediate goal …

Electroencephalogram (EEG) signals contain vital information on the electrical activities of
the brain and are widely used to aid epilepsy analysis. A challenging element of epilepsy …

Since the discovery of the EEG principles by Berger in the 20's, procedures for artifact
removal have been essential in its pre-processing. In literature, diverse approaches based …

Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting
state are increasingly used to study functional connectivity and network topology. Moreover …