Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …

Electroencephalogram (EEG), boasting the advantages of portability, low cost, and
hightemporal resolution, is a non-invasive brain-imaging modality that can be used to …

Objective. Deep learning (DL) networks are increasingly attracting attention across various
fields, including electroencephalography (EEG) signal processing. These models provide …

In the past decade, brain and autonomic nervous system activity measurement received
increasing attention in the study of software engineering (SE). This paper presents a …

Electroencephalography (EEG) is the signal of intrigue that has immense application in the
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …

Objective: Blink-related features derived from electroencephalography (EEG) have recently
arisen as a meaningful measure of driver's cognitive state. Combined with band power …

Objective: Recent advances in development of low-cost single-channel
electroencephalography (EEG) headbands have opened new possibilities for applications …

A brain-computer interface (BCI) provides a way to develop interaction between a brain and
a computer. The communication is developed as a result of neural responses generated in …

It is a fact that contamination of EEG by ocular artifacts reduces the classification accuracy of
a brain‐computer interface (BCI) and diagnosis of brain diseases in clinical research …

In this paper, a novel multi-module neural network (MMNN) is proposed to remove ocular
artifacts (OAs) and myogenic artifacts (MAs) from noisy single-channel …