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

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

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

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

When infants and adults communicate, they exchange social signals of availability and
communicative intention such as eye gaze. Previous research indicates that when …

Dual-process models of cognition suggest that there are two types of thought: autonomous
Type 1 processes and working memory dependent Type 2 processes that support …

Objective. The electroencephalogram (EEG) is an essential neuro-monitoring tool for both
clinical and research purposes, but is susceptible to a wide variety of undesired artifacts …

Electroencephalogram (EEG), boasting the advantages of portability, low cost, and
hightemporal resolution, is a non-invasive brain-imaging modality that can be used to …

Speech is a complex process involving a wide range of biosignals, including but not limited
to acoustics. These biosignals-stemming from the articulators, the articulator muscle …

Electroencephalography (EEG) recordings are often contaminated by muscle artifacts. In the
literature, a number of methods have been proposed to deal with this problem. Yet most …