The paper presents the results of a comparative study of the artifact subspace re-
construction (ASR) method and two other popular methods dedicated to correct EEG …

The common spatial pattern (CSP) is a very effective feature extraction method in motor
imagery based brain computer interface (BCI), but its performance depends on the selection …

Abstract The decoding of Motor Imagery EEG (MI-EEG) is the most crucial part of biosignal
processing in the Brain-computer Interface (BCI) system. The traditional recognition mode is …

Feature selection plays a critical role in the application of Brain Computer Interface (BCI)
systems. Many methods have been used to solve the feature selection problem, but they …

Providing significant features to the classifier is essential for the enhancement of
classification accuracy. To meet this demand, feature selection plays a vital role in the field …

The selection of time segment and frequency band always play a vital role in the decoding of
Motor Imagery Tasks (MI-tasks), especially for the feature extraction of MI …

For treatment of mental and brain diseases and diagnosis of abnormalities
electroencephalogram (EEG) is an important measurement of brain activity. Feature …

Brain computer interface (BCI) systems have been regarded as a new way of
communication for humans. In this research, common methods such as wavelet transform …

The purpose of the article is to check whether the method of estimating EEG signal energy,
treated as a feature, has an impact on the classification accuracy in BCI systems. The …

Because the signal-to-noise ratio of Electroen-cephalograph (EEG) signals of motor
imagination is low, unstable and significant different, it has a negative impact on EEG …