Removal of muscular artifacts in EEG signals: a comparison of linear decomposition methods

Removal of muscular artifacts in EEG signals: a comparison of linear decomposition methods

Abstract The most common approach to reduce muscle artifacts in electroencephalographic signals is to linearly decompose the signals in order to separate artifactual from neural sources, using one of several variants of independent component analysis (ICA). Here we compare three of the most commonly...

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Bibliographic Details
Main Authors: Laura Frølich, Irene Dowding
Format: Article
Language:English
Published: SpringerOpen 2018-01-01
Series:Brain Informatics
Subjects:
Electroencephalogram (EEG)
Artifact removal
Muscle artifacts
Blind source separation (BSS)
Independent component analysis (ICA)
Filtering
Online Access:http://link.springer.com/article/10.1007/s40708-017-0074-6

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http://link.springer.com/article/10.1007/s40708-017-0074-6

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