An independent component analysis-based approach on ballistocardiogram artifact removing

Ennio Briselli, Girolamo Garreffa, Luigi Bianchi, Marta Bianciardi, Emiliano Macaluso, Manuel Abbafati, Maria Grazia Marciani, Bruno Maraviglia

Research output: Contribution to journalArticlepeer-review


Interest about simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data acquisition has rapidly increased during the last years because of the possibility that the combined method offers to join temporal and spatial resolution, providing in this way a powerful tool to investigate spontaneous and evoked brain activities. However, several intrinsic features of MRI scanning become sources of artifacts on EEG data. Noise sources of a highly predictable nature such as those related to the pulse MRI sequence and those determined by magnetic gradient switching during scanning do not represent a major problem and can be easily removed. On the contrary, the ballistocardiogram (BCG) artifact, a large signal visible on all EEG traces and related to cardiac activity inside the magnetic field, is determined by sources that are not fully stereotyped and causing important limitations in the use of artifact-removing strategies. Recently, it has been proposed to use independent component analysis (ICA) to remove BCG artifact from EEG signals. ICA is a statistical algorithm that allows blind separation of statistically independent sources when the only available information is represented by their linear combination. An important drawback with most ICA algorithms is that they exhibit a stochastic behavior: each run yields slightly different results such that the reliability of the estimated sources is difficult to assess. In this preliminary report, we present a method based on running the FastICA algorithm many times with slightly different initial conditions. Clustering structure in the signal space of the obtained components provides us with a new way to assess the reliability of the estimated sources.

Original languageEnglish
Pages (from-to)393-400
Number of pages8
JournalMagnetic Resonance Imaging
Issue number4
Publication statusPublished - May 2006


  • Artifacts
  • BCG
  • EEG
  • FastICA
  • MRI

ASJC Scopus subject areas

  • Biophysics
  • Clinical Biochemistry
  • Structural Biology
  • Radiology Nuclear Medicine and imaging
  • Condensed Matter Physics

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