• DocumentCode
    1393908
  • Title

    Denoising and Frequency Analysis of Noninvasive Magnetoencephalography Sensor Signals for Functional Brain Mapping

  • Author

    Ukil, Abhisek

  • Author_Institution
    Integrated Sensor Syst. Group, ABB Corp. Res., Baden-Daettwil, Switzerland
  • Volume
    12
  • Issue
    3
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    447
  • Lastpage
    455
  • Abstract
    Magnetoencephalography (MEG) is an important noninvasive, nonhazardous technology for functional brain mapping, measuring the magnetic fields due to the intracellular neuronal current flow in the brain. However, most often, the inherent level of noise in the MEG sensor data collection process is large enough to obscure the signal(s) of interest. In this paper, a denoising technique based on the wavelet transform and the multiresolution signal decomposition technique along with thresholding is presented, substantiated by application results. Thereafter, different frequency analysis are performed on the denoised MEG signals to identify the major frequencies of the brain oscillations present in the denoised signals. Time-frequency plots (spectrograms) of the denoised signals are also provided.
  • Keywords
    brain; magnetic field effects; magnetoencephalography; medical signal processing; neurophysiology; signal denoising; wavelet transforms; MEG sensor data collection processing; brain oscillations; denoising analysis; frequency analysis; functional brain mapping; intracellular neuronal current flow; multiresolution signal decomposition technique; noninvasive magnetoencephalography sensor signals; time-frequency plots; wavelet transform; Magnetic recording; Magnetic resonance imaging; Noise reduction; Signal resolution; Superconducting magnets; Wavelet transforms; Alpha wave; beta wave; brain signal processing; gamma wave; high beta wave; signal denoising; spectrogram; theta wave; threshold; time-frequency plot; wavelet transform;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2010.2096465
  • Filename
    5657225