title: Decomposition of biomedical signals in spatial and time-frequency modes.
abstract: OBJECTIVE
  The purpose of this paper is to introduce a new method for spatial-time-frequency analysis of multichannel biomedical data. We exemplify the method for data recorded with a 31-channel Philips biomagnetometer.
  
  
  METHODS
  The method creates approximations and decompositions of spatiotemporal signal distributions using elements (atoms) chosen from a very large and redundant set (dictionary). The method is based on the Matching Pursuit algorithm, but it uses atoms that are distributed both in time and space (instead of only time-distributed atoms in standard Matching Pursuit). The time-frequency distribution of signal components is described by Gabor atoms and their spatial distribution is modeled by spatial modes. The spatial modes are created with the help of Bessel functions. Two versions of the method, differing in the definition of spatial properties of the atoms, are presented.
  
  
  RESULTS
  The technique was validated on simulated data and real magnetic field data. It was used for removal of powerline noise from multichannel magnetoencephalography data, extraction of high-frequency somatosensory evoked fields and for separation of partially overlapping T- and U-waves in magnetocardiography.
  
  
  CONCLUSIONS
  The method allows for parameterization of multichannel data in the time-frequency as well as in the spatial domains. It thus can be used for signal preserving filtering simultaneously in time, frequency, and space. Applications are e.g. the elimination of artifact components, extraction of components with biological meaning, and data exploration.
authors.affiliation: Institute of Biomedical Engineering and Informatics, Computer Science and Automation Faculty, Technische Universität Ilmenau, Gustav-Kirchhoff Str. 2, 98693 Ilmenau, Germany. Maciej.Gratkowski@tu-ilmenau.de
authors.forename: M
authors.initials: M
authors.lastname: Gratkowski
authors.forename: J
authors.initials: J
authors.lastname: Haueisen
authors.forename: L
authors.initials: L
authors.lastname: Arendt-Nielsen
authors.forename: A
authors.initials: A
authors.lastname: Cn Chen
authors.forename: F
authors.initials: F
authors.lastname: Zanow
mesh_terms: D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007089:Image Enhancement; D015225:Magnetoencephalography / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013997:Time Factors