One of the essential challenges in brain–computer interface is to classify motor imagery (MI)
signals. In this paper, an ensemble SVM-based voting system is proposed. In each line of …

Granger-causality-based brain network analysis has been widely applied in EEG-based
neuroscience researches and clinical diagnoses, such as motor imagery emotion analysis …

EEG data obtained from the scalp using the electrodes, usually gets contaminated by
various artifacts like muscle artifact, line interference artifact, ocular artifact, and others. The …

The performance of vehicle detection system is often affected by both internal and external
noise. In this paper, a novel vehicle detection scheme called vehicle detector based on EMD …

Abstract Motor Imagery-Brain-Computer Interface (MI-BCI) enables people with disabilities
to communicate through a channel that does not require them to use their muscles. We …

Electroencephalography (EEG) is a commonly used technique for assessing brain activity
through electrodes placed on the scalp. EEG signals hold significant information often …

Emotions are a human sensation capable of impacting an individual's quality of life in a
positive as well as a negative manner. The capacity to identify various categories of …

With the advent of the big data era, the ever-increasing accumulated financial data plays a
significant role in people's daily life. The ensemble methods are the most efficient and …

At the child brain facility at the Erasmus Medical Centre, multiple tests are performed with
children who have one of several disorders. Two of these tests are done with …

Inaccuracies in removing Ocular Artifact (OA) in EEG signals can cause loss of information in
EEG signals. Several previous methods utilize the feature of OA to detect OA and then …