In this study, three popular signal processing techniques (Empirical Mode Decomposition,
Discrete Wavelet Transform, and Wavelet Packet Decomposition) were investigated for the …

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

Electroencephalography (EEG) is a noninvasive electrophysiological monitoring technique
that records the electrical activities of the brain from the scalp using electrodes. EEG is not …

Motor deficiencies constitute a significant problem affecting millions of people worldwide.
Such people suffer from a debility in daily functioning, which may lead to decreased and …

Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …

Abstract Decryption of Motor Imagery (MI) activity from an Electroencephalogram (EEG) data
is a significant part of the Brain-Computer Interface (BCI) technology that allows motor …

The feature extraction technique plays a vital role in obtaining better classification accuracy.
In this paper, a novel framework is proposed, which develops two‐dimensional (2D) images …

In the last decade of the XX-th century, several academic centers have launched intensive
research programs on the brain-computer interface (BCI). The current state of research …

Feature selection is crucial to develop a brain computer interface (BCI) system which has
high classification accuracy and less computational complexity in especially a large feature …

The basis of the work of electroencephalography (EEG) is the registration of electrical
impulses from the brain using a special sensor or electrode. This method is used to treat and …