• DocumentCode
    1613022
  • Title

    Decomposition of Evoked Potentials using Peak Detection and the Discrete Wavelet Transform

  • Author

    McCooey, Conor ; Kumar, Dinesh Kant ; Cosic, Irena

  • Author_Institution
    R. Melbourne Inst. of Technol., Vic.
  • fYear
    2006
  • Firstpage
    2071
  • Lastpage
    2074
  • Abstract
    A new method of viewing evoked potential data is described. This method, called the peak detection method, is based on singularity detection using the discrete wavelet transform. The peaks and troughs of raw visual evoked potential data are identified and characterized using the algorithms of this method, resulting in a linear decomposition of the recording into sets of individual peaks. The individual peaks are then added together, averaged and compared to the ensemble average signal. The peak detection method correlates strongly to the ensemble average showing that this method retains the same evoked potential signal profile
  • Keywords
    discrete wavelet transforms; medical signal detection; medical signal processing; visual evoked potentials; discrete wavelet transform; linear decomposition; peak detection; singularity detection; visual evoked potential; Australia; Biomedical engineering; Design methodology; Discrete wavelet transforms; Disk recording; Electroencephalography; Logic arrays; Signal generators; Spline; Wavelet domain; Averaging; Discrete Wavelet Transform; EEG; Singularity Detection; Visual Evoked Potentials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1616866
  • Filename
    1616866