Emotion recognition based on electroencephalography (EEG) signal features is now one of
the booming big data research areas. As the number of commercial EEG devices in the …

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

Event-related potentials (ERPs) recorded from the human scalp can provide important
information about how the human brain normally processes information and about how this …

Brain-electric correlates of reading have traditionally been studied with word-by-word
presentation, a condition that eliminates important aspects of the normal reading process …

Eye movements cause changes to the electric fields around the eyes, and consequently
over the scalp. As a result, EEG recordings are often significantly distorted, and their …

Combining EEG with eye-tracking is a promising approach to study neural correlates of
natural vision, but the resulting recordings are also heavily contaminated by activity of the …

Review and analysis of continuous EEG recordings may be impeded by physiological
artifacts such as blinks, eye movements, or cardiac activity. Spatial filters based on artifact …

Previously published methods correct eye artifacts by subtracting proportions of the EOG
from EEG electrodes. The implicit assumption made by these methods is that the EOG …

Eye activity is one of the main sources of artefacts in EEG and MEG recordings. A new
approach to the correction of these disturbances is presented using the statistical technique …

Ever since Berger (1929) demonstrated that it is possible to record the electrical activity of
the brain by placing electrodes on the surface of the scalp, there has been considerable …