• DocumentCode
    2606540
  • Title

    EOG segmentation using fast algorithms

  • Author

    Buzenac, V. ; Settineri, R. ; Najim, M. ; Paty, J.

  • Author_Institution
    Equipe Signal et Image de l´´ENSERB, Univ. de Bordeaux I, Talence, France
  • fYear
    1993
  • fDate
    3-6 May 1993
  • Firstpage
    826
  • Abstract
    A new method is presented for segmentation of rapidly time-varying signals based on fast least squares algorithms, due to their low complexity. The detection test used is based on the likelihood variable which appears explicitly in the fast algorithms. In order to show the performances of the method, it is applied to E.O.G. (electrooculograms) signals
  • Keywords
    electroencephalography; least squares approximations; medical signal processing; EOG segmentation; EOG signals; detection test; electrooculograms; least squares algorithms; likelihood variable; rapidly time-varying signals; Autocorrelation; Electrooculography; Error correction; Image segmentation; Kalman filters; Least squares methods; Nonlinear filters; Resonance light scattering; Testing; Transversal filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-7803-1281-3
  • Type

    conf

  • DOI
    10.1109/ISCAS.1993.393850
  • Filename
    393850