Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics

Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS& HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG.

Source: Computers in Biology and Medicine - June 21, 2017 Category: Bioinformatics Authors: Xun Chen, Aiping Liu, Qiang Chen, Yu Liu, Liang Zou, Martin J. McKeown Source Type: research