A robust independent component analysis algorithm for removing ballistocardiogram artifacts from EEG and fMRI recordings

Tiziana Franchin, A. M. Bianchi, V. Cannatà, E. Genovese, F. Nocchi, S. Cerutti

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

Abstract

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings provide complementary advantages with regard to the temporal and spatial resolution of brain activity. This methodology still now suffers from several artifacts, such as the gradient, the ballistocardiogram (BCG) and electrooculogram (EOG). A number of procedures have been developed in recent years for removing BCG artifacts and the usefulness of Independent Component Analysis (ICA) in this purpose was largely discussed and demonstrated. The aim of this study is to propose a more efficient and robust independent component analysis algorithm (RobustICA) for removing BCG and EOG artifacts. The algorithm has been validated on EEG datasets acquired inside the static magnetic field of a 1,5 T RM scanner and its performances were compared with those of other already applied processing methods (Optimal Basis Set, FastICA).

Original languageEnglish
Title of host publicationIFMBE Proceedings
Pages1286-1289
Number of pages4
Volume22
DOIs
Publication statusPublished - 2008
Event4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008 - Antwerp, Belgium
Duration: Nov 23 2008Nov 27 2008

Other

Other4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008
CountryBelgium
CityAntwerp
Period11/23/0811/27/08

Keywords

  • Ballistocardiogram artifact
  • EEG
  • FMRI
  • ICA

ASJC Scopus subject areas

  • Biomedical Engineering
  • Bioengineering

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