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 …

Objective. Classification of electroencephalography (EEG)-based motor imagery (MI) is a
crucial non-invasive application in brain–computer interface (BCI) research. This paper …

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

Electroencephalography (EEG) is the most popular brain activity recording technique used
in wide range of applications. One of the commonly faced problems in EEG recordings is the …

Background Electroencephalographic data are easily contaminated by signals of non-neural
origin. Independent component analysis (ICA) can help correct EEG data for such artifacts …

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

Electroencephalography (EEG), as a non-invasive modality, enables the representation of
the underlying neuronal activities as electrical signals with high temporal resolution. In …

Objective: Electroencephalography (EEG) is a non-invasive technique used to record
cortical neurons' electrical activity using electrodes placed on the scalp. It has become a …