Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …

Common spatial pattern (CSP) technique has been very popular in terms of
electroencephalogram (EEG) features extraction in motor imagery (MI)-based brain …

One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled
electroencephalogram (EEG) representation method which can preserve not only temporal …

Common spatial pattern (CSP)-based spatial filtering has been most popularly applied to
electroencephalogram (EEG) feature extraction for motor imagery (MI) classification in brain …

Motor Imagery (MI) paradigm is critical in neural rehabilitation and gaming. Advances in
brain-computer interface (BCI) technology have facilitated the detection of MI from …

Abstract Motor Imagery Brain Computer Interface (MI-BCI) provides a non-muscular channel
for communication to those who are suffering from neuronal disorders. The designing of an …

Objective. Learning the structures and unknown correlations of a motor imagery
electroencephalogram (MI-EEG) signal is important for its classification. It is also a major …

The common spatial patterns (CSP) algorithm is the most popular spatial filtering method
applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain …

In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be
extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) …