Practical Denoising of MEG Data Using Wavelet Transform

  • Abhisek Ukil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)


Magnetoencephalography (MEG) is an important noninvasive, non-hazardous technology for functional brain mapping, measuring the magnetic fields due to the intracellular neuronal current flow in the brain. However, the inherent level of noise in the data collection process is large enough to obscure the signal(s) of interest most often. In this paper, a practical denoising technique based on the wavelet transform and the multiresolution signal decomposition technique is presented. The proposed technique is substantiated by the application results using three different mother wavelets on the recorded MEG signal.


Discrete Wavelet Transform Wavelet Transform Finite Impulse Response Independent Component Analysis Mother Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Abhisek Ukil
    • 1
  1. 1.Tshwane University of TechnologyPretoriaSouth Africa

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