This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …

As it was mentioned in the previous part of this work (Part I)—the advanced signal
processing methods are one of the quickest and the most dynamically developing scientific …

Emotion modeling and recognition has drawn extensive attention from disciplines such as
psychology, cognitive science, and, lately, engineering. Although a significant amount of …

The physiological artifacts such as electromyogram (EMG) and electrooculogram (EOG)
remain a major problem in electroencephalogram (EEG) research. A number of techniques …

Wide-area synchrophasor ambient measurements provide a valuable data source for real-
time oscillation mode monitoring and analysis. This paper introduces a novel method for …

There are many sources of interference encountered in the electroencephalogram (EEG)
recordings, specifically ocular, muscular, and cardiac artifacts. Rejection of EEG artifacts is …

This paper presents a data adaptive filtering approach to separate the electrooculograph
(EOG) artifact from the recorded electroencephalograph (EEG) signal. Empirical mode …

Electroencephalography (EEG) data are used to design useful indicators that act as proxies
for detecting humans' mental activities. However, these electrical signals are susceptible to …

Signals associated with eye blinks (230–350 micro-volts) are orders of magnitude larger
than electric potentials (7–20 micro-volts) generated on the scalp because of cortical activity …

Abstract Background The visual evoked Electroencephalogram (EEG) signals are useful
indicators to explore the hidden neural circuitry in human brain. But these signals are highly …