• DocumentCode
    726804
  • Title

    Spectral analysis of visual evoked potentials

  • Author

    Dobrowolski, Andrzej P. ; Okon, Marta

  • Author_Institution
    Fac. of Electron., Mil. Univ. of Technol., Warsaw, Poland
  • fYear
    2015
  • fDate
    10-12 June 2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The paper presents a conception of classification method of Visual Evoked Potentials (VEP) to physiological or pathological case based on power spectral parameters. The authors have verified their concept through a series of numerical experiments performed using a dedicated application. As a result of experiments, the final method provided only 4 cases of wrong classification among training data (6%) and 13 among the testing data (43%).
  • Keywords
    medical signal processing; principal component analysis; signal classification; spectral analysis; support vector machines; visual evoked potentials; VEP; classification method; dedicated application; pathological case; physiological case; power spectral parameters; spectral analysis; testing data; training data; visual evoked potentials; Electric potential; Gravity; Pathology; Principal component analysis; Spectral analysis; Support vector machines; Visualization; Principal Component Analysis; Support Vector Machine; biomedical signal processing; spectral analysis; visual evoked potential;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Symposium (SPSympo), 2015
  • Conference_Location
    Debe
  • Type

    conf

  • DOI
    10.1109/SPS.2015.7168275
  • Filename
    7168275