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 …

Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

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

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

Electroencephalography (EEG) has been widely used for studying brain function. As cortical
signals recorded by the EEG are very weak, they are often obscured by motion artifacts and …

Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts,
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …

Electroencephalogram (EEG) is the record of cerebral activity, the electric potential of
cerebral activity is of low amplitude, and less frequency ranges between 4 to 60 Hz, which …

A common drawback of EEG-based emotion recognition is that volume conduction effects of
the human head introduce interchannel dependence and result in highly correlated …

Brain–computer interface (BCI) actively translates the brain signals into executable actions
by establishing direct communication between the human brain and external devices …

Objective. Electroencephalography (EEG) cleaning has been a longstanding issue in the
research community. In recent times, huge leaps have been made in the field, resulting in …