A brain computer interface (BCI) framework uses computer algorithms to detect mental
activity patterns and manipulate external devices. Because of its simplicity and non …

Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …

Objective. Most current electroencephalography (EEG)-based brain–computer interfaces
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …

A brain-computer interface (BCI) systems permit encephalic activity to solely control
computers or external devices. Accordingly, people suffering from neuromuscular diseases …

In this paper we review classification algorithms used to design brain–computer interface
(BCI) systems based on electroencephalography (EEG). We briefly present the commonly …

Brain–computer interface (BCI) technology has been studied with the fundamental goal of
helping disabled people communicate with the outside world using brain signals. In …

Classification of EEG signals extracted during mental tasks is a technique for designing
brain computer interfaces (BCI). We classify EEG signals that were extracted during mental …

ABSTRACT Brain Computer Interface (BCI) is often directed at mapping, assisting, or
repairing human cognitive or sensory-motor functions. Electroencephalogram (EEG) is a …

This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …

Background Brain–computer interface (BCI) is a new communication pathway for users with
neurological deficiencies. The implementation of a BCI system requires complex …