Clustering of Spectral Patterns Based on EMD Components of EEG Channels with Applications to Neurophysiological Signals Separation

  • Tomasz M. Rutkowski
  • Andrzej Cichocki
  • Toshihisa Tanaka
  • Anca L. Ralescu
  • Danilo P. Mandic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5506)


The notion of information separation in electrophysiological recordings is discussed. Whereas this problem is not entirely new, a novel approach to separate muscular interference from brain electrical activity observed in form of EEG is presented. The EEG carries brain activity in form of neurophysiological components which are usually embedded in much higher in power electrical muscle activity components (EMG, EOG, etc.). A novel multichannel EEG analysis approach is proposed in order to discover representative components related to muscular activity which are not related to ongoing brain activity but carry common patterns resulting from non-brain related sources. The proposed adaptive decomposition approach is also able to separate signals occupying same frequency bands what is usually not possible with contemporary methods.


Empirical Mode Decomposition Instantaneous Frequency Intrinsic Mode Function Zero Crossing Intrinsic Mode Function 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Tomasz M. Rutkowski
    • 1
  • Andrzej Cichocki
    • 1
  • Toshihisa Tanaka
    • 2
    • 1
  • Anca L. Ralescu
    • 3
  • Danilo P. Mandic
    • 4
  1. 1.RIKEN Brain Science Institute, Wako-shiSaitamaJapan
  2. 2.Tokyo University of Agriculture and TechnologyTokyoJapan
  3. 3.Computer Science DepartmentUniversity of CincinnatiOhioUSA
  4. 4.Department of Electrical and Electronic EngineeringImperial College LondonUK

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