Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.
Journal:
Journal of neural engineering
Published Date:
Aug 1, 2017
Abstract
OBJECTIVE: Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present.
