• DocumentCode
    1239099
  • Title

    H∞ adaptive filters for eye blink artifact minimization from electroencephalogram

  • Author

    Puthusserypady, S. ; Ratnarajah, T.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
  • Volume
    12
  • Issue
    12
  • fYear
    2005
  • Firstpage
    816
  • Lastpage
    819
  • Abstract
    Two adaptive algorithms (time varying and exponentially weighted) based on the H∞ principles are proposed for the minimization of electrooculogram (EOG) artifacts from corrupted electroencephalographic signals. Performance of the proposed algorithms are compared with the least-mean-square (LMS) algorithm. Improvements in the output signal-to-noise ratio along with time plots are used for the comparison. It is found that the H∞-based algorithms effectively minimize the EOG artifacts and always outperform the LMS algorithm.
  • Keywords
    H∞ optimisation; adaptive filters; biomedical equipment; electro-oculography; electroencephalography; medical signal processing; minimisation; neurophysiology; EEG; EOG; H∞ adaptive filter; electroencephalogram; electrooculogram; eye blink artifact; minimization; Adaptive algorithm; Adaptive filters; Brain modeling; Electroencephalography; Electrooculography; Filtering algorithms; Independent component analysis; Least squares approximation; Minimization methods; Uncertainty; Blink artifacts; electroencephalogram (EEG);
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2005.859526
  • Filename
    1542107
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1239099