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

Laura Frølich,Irene Dowding

doi:10.1007/s40708-017-0074-6

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 used ICA methods (extended Infomax, FastICA and TDSEP) with two other linear decomposition methods (Fourier-ICA and spatio-spectral decomposition) suitable for the extraction of oscillatory activity. We evaluate the methods’ ability to remove event-locked muscle artifacts while maintaining event-related desynchronization in data from 18 subjects who performed self-paced foot movements. We find that all five analyzed methods drastically reduce the muscle artifacts. For the three ICA methods, adequately high-pass filtering is very important. Compared to the effect of high-pass filtering, differences between the five analyzed methods were small, with extended Infomax performing best.

Highlights

The removal of undesired artifacts from the electroencephalogram (EEG) is a major preprocessing step for most EEG analysis
As independent component analysis (ICA) and other linear decomposition methods are the most widely used tool to reduce muscle artifacts in EEG signals, many researchers wonder which one to choose in practice
We resorted to a self-paced movement paradigm which induces a decrease in rhythmic activity, as opposed to muscle artifacts which typically increase spectral power

Summary

Introduction

The removal of undesired artifacts from the electroencephalogram (EEG) is a major preprocessing step for most EEG analysis. Such artifacts stem from eye and muscle movement, the heart beat or external technical sources. We are concerned with the removal of muscle artifacts. These are typically caused by muscle activity near the head, such as swallowing or head movements, and are characterized by high-frequency activity ([ 20 Hz) [1]. Because muscle activity arises from different type of muscle groups, muscle artifacts are harder to stereotype than eye artifacts (cf [2,3,4]).

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