Nowadays, the interest in the Brain-Computer Interfacing (BCI) domain is continuously
growing, only judging by the number of BCI related papers published or presented in neuro …

Electroencephalogram (EEG) is one of the common modalities of monitoring the mental
activities. Owing to the non-invasive availability of this system, its applicability has seen …

Overview: The electroencephalographic (EEG) signals provide highly informative data on
brain activities and functions. Therefore, it is possible to extract a great variety of features …

Recently, it has been discovered that EEG signals have enormous potential to be used as
biometric authentication. Although, its practical implementation is limited due to the intricate …

In this study, the effects of feature selection on classification ofthe electrical signals
generated in the brain during numerical and verbaloperations are investigated. 18 healthy …

Nowadays Electroencephalogram (EEG) devices allow the recording of signals that can be
used to extract information necessary to identify different types of cognitive processes. In …

Feature selection is an important step regarding Electroencephalogram (EEG) classification,
for a Brain-Computer Interface (BCI) systems, related to Motor Imagery (MI), due to large …

In pattern identification, embedded Feature Selection (FS) determines a detailed data
description and an efficient and accurate classification. Most Genetic Algorithm (GA) based …

Although numerous efforts have been made to develop feature selection framework which is
efficient in Big Data technology, complexity of processing big data remains a significant …

In this study, the effects of feature selection on classification of the electrical signals
generated in the brain during numerical and verbal operations are investigated. 18 healthy …