Electroencephalography (EEG) is a non-invasive measurement method for brain activity.
Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural …

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 …

It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear
behaviours. Here we challenge this assumption by leveraging mathematical models derived …

Objective. Brain–computer interfaces (BCI) enable direct communication with a computer,
using neural activity as the control signal. This neural signal is generally chosen from a …

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 …

This paper will focus on electroencephalogram (EEG) signal analysis with an emphasis on
common feature extraction techniques mentioned in the research literature, as well as a …

ERPLAB toolbox is a freely available, open-source toolbox for processing and analyzing
event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely …

Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …

Mild cognitive impairment (MCI) can be an indicator representing the early stage of
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …

Classification of electroencephalogram (EEG) signals is an important task in the brain
computer interface system. This paper presents two combination strategies of feature …