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

Electroencephalography (EEG) has been widely used for studying brain function. As cortical
signals recorded by the EEG are very weak, they are often obscured by motion artifacts and …

Background Electroencephalographic data are easily contaminated by signals of non-neural
origin. Independent component analysis (ICA) can help correct EEG data for such artifacts …

Detecting artifacts produced in EEG data by muscle activity, eye blinks and electrical noise is
a common and important problem in EEG research. It is now widely accepted that …

Independent component analysis (ICA) has been proven useful for suppression of artifacts
in EEG recordings. It involves separation of measured signals into statistically independent …

The electroencephalogram (EEG) is often contaminated by muscle artifacts. In this paper, a
new method for muscle artifact removal in EEG is presented, based on canonical correlation …

Motivation: The success or failure of an epilepsy surgery depends greatly on the localization
of epileptic focus (origin of a seizure). We address the problem of identification of a seizure …

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

Results obtained using continuous and discrete wavelet transforms as applied to problems
in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for …

OBJECTIVE: To devise an automated system to remove artifacts from ictal scalp EEG, using
independent component analysis (ICA). METHODS: A Bayesian classifier was used to …