Rejection of artifact sources in magneto encephalogram background activity using independent component analysis

Javier Escudero*, Roberto Hornero, Daniel Abasolo, Jesus Poza, Alberto Fernandez, Miguel Lopez

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The aim of this pilot study was to assess the usefulness of independent component analysis (ICA) to detect cardiac artifacts and power line interferences in magnetoencephalogram (MEG) recordings. We recorded MEG signals from six subjects with, a 148-channel whole-head magnetometer (MAGNES 2500 WH, 4D Neuroimaging). Epochs of 50 s with power line noise, cardiac, and ocular artifacts were selected for analysis. We applied a statistical criterion to determine the number of sources, and a robust ICA algorithm to decompose the MEG epochs. Skewness, kurtosis, and a spectral metric were used to mark the studied artifacts. We found that the power fine interference could be easily detected by its frequency characteristics. Moreover, skewness outperformed kurtosis when identifying the cardiac artifact.

Original languageEnglish
Title of host publication2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-15
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages273-276
Number of pages4
ISBN (Print)978-1-4244-0032-4
Publication statusPublished - 2006
Event28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society - New York, United Kingdom
Duration: 30 Aug 20063 Sep 2006

Conference

Conference28th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society
CountryUnited Kingdom
Period30/08/063/09/06

Keywords

  • BLIND SOURCE SEPARATION
  • OCULAR ARTIFACTS
  • IDENTIFICATION
  • REMOVAL
  • SIGNALS
  • EEG
  • FIELDS
  • BRAIN

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