• DocumentCode
    140092
  • Title

    Comparison study of seizure detection using stationary and nonstationary methods

  • Author

    Ying Li ; Yue-Loong Hsin ; Wentai Liu

  • Author_Institution
    Bioeng. Dept., Univ. of California, Los Angeles, Los Angeles, CA, USA
  • fYear
    2014
  • fDate
    26-30 Aug. 2014
  • Firstpage
    3272
  • Lastpage
    3275
  • Abstract
    We present an accurate seizure detection algorithm, and make a detailed comparison of two frequency analysis methods: a widely used stationary method - Fast Fourier Transform (FFT) and a relatively new nonstationary method - Hilbert-Huang Transform (HHT). Two public databases and one our own database were tested. The results show that our algorithm has very high accuracy compared with the state-of-the-art. More interestingly, it shows that the nonstationary method HHT offers better performance than the stationary method FFT in seizure detection. Therefore we propose that we should pay attention to the nonstationarity of EEG signal, since the “stationary assumption” may introduce some inaccuracy.
  • Keywords
    Hilbert transforms; electroencephalography; fast Fourier transforms; frequency-domain analysis; medical disorders; medical signal detection; EEG signal nonstationarity; Fast Fourier Transform; Hilbert-Huang Transform; frequency analysis methods; nonstationary method HHT; public databases; seizure detection algorithm; stationary assumption; stationary method FFT; Accuracy; Classification algorithms; Databases; Electroencephalography; Feature extraction; Time-frequency analysis; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2014.6944321
  • Filename
    6944321