Applying Independent Component Analysis to the Artifact Detection Problem in Magnetoencephalogram Background Recordings

  1. Escudero, Javier 1
  2. Hornero, Roberto 1
  3. Abásolo, Daniel 1
  4. Poza, Jesús 1
  5. Fernández, Alberto 1
  1. 1 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

Libro:
Encyclopedia of Healthcare Information Systems

Año de publicación: 2008

Páginas: 84-92

Tipo: Capítulo de Libro

DOI: 10.4018/978-1-59904-889-5.CH012 GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

The analysis of the electromagnetic brain activity can provide important information to help in the diagnosis of several mental diseases. Both electroencephalogram (EEG) and magnetoencephalogram (MEG) record the neural activity with high temporal resolution (Hämäläinen, Hari, Ilmoniemi, Knuutila, & Lounasmaa, 1993). Nevertheless, MEG offers some advantages over EEG. For example, in contrast to EEG, MEG does not depend on any reference point. Moreover, the magnetic fields are less distorted than the electric ones by the skull and the scalp (Hämäläinen et al., 1993). Despite these advantages, the use of MEG data involves some problems. One of the most important difficulties is that MEG recordings may be severely contaminated by additive external noise due to the intrinsic weakness of the brain magnetic fields. Hence, MEG must be recorded in magnetically shielded rooms with low-noise SQUID (Superconducting QUantum Interference Devices) gradiometers (Hämäläinen et al., 1993).