• DocumentCode
    2484252
  • Title

    Removal of Ocular Artifacts from EEG Signals Using Adaptive Threshold PCA and Wavelet Transforms

  • Author

    Babu, P. Ashok ; Prasad, K.V.S.V.R.

  • Author_Institution
    Dept. of Electron. & Commun. Eng., NREC, Hyderabad, India
  • fYear
    2011
  • fDate
    3-5 June 2011
  • Firstpage
    572
  • Lastpage
    575
  • Abstract
    It becomes more difficult to identify and analyze the Electroencephalogram (EEG) signals when it is corrupted by eye movements and eye blinks. This paper gives the different methods how to remove the artifacts in EEG signals. In this paper we proposed wavelet based threshold method and Principal Component Analysis (PCA) based adaptive threshold method to remove the ocular artifacts. Compared to the wavelet threshold method PCA based adaptive threshold method will gives the better PSNR value and it will decreases the elapsed time.
  • Keywords
    discrete wavelet transforms; electroencephalography; eye; principal component analysis; signal detection; EEG signal; PSNR value; adaptive threshold PCA; electroencephalogram signal; eye blink; eye movement; ocular artifact; principal component analysis; wavelet transform; Electroencephalography; Electrooculography; Noise measurement; Principal component analysis; Wavelet analysis; Wavelet transforms; Discrete Wavelet Transform (DWT); Electroencephalogram (EEG); PCA based Adaptive threshold algorithm; Principal Component Analysis (PCA); Stationary Wavelet Transform (SWT);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Network Technologies (CSNT), 2011 International Conference on
  • Conference_Location
    Katra, Jammu
  • Print_ISBN
    978-1-4577-0543-4
  • Electronic_ISBN
    978-0-7695-4437-3
  • Type

    conf

  • DOI
    10.1109/CSNT.2011.122
  • Filename
    5966512