• DocumentCode
    3363395
  • Title

    Comparison of various time/frequency distributions (classical and signal-dependent) applied to synthetic uterine EMG signals

  • Author

    Devedeux, Dominique ; Duchêne, Jacques

  • Author_Institution
    Dept. of Biol. Eng., Compiegne Univ., France
  • fYear
    1994
  • fDate
    25-28 Oct 1994
  • Firstpage
    572
  • Lastpage
    575
  • Abstract
    Synthetic signals simulating uterine EHG are created in order to compare and validate several time/frequency distributions (TFD): we tested autoregressive spectra, short time Fourier transform, smooth pseudo Wigner Ville, exponential and cone shaped kernel distributions, as well as a signal-dependent method. Specific criteria were especially designed in order to quantify either the overall quality of the TFDs or their capability of tracking efficiently the evolution of the main spectral peak. Both the autoregressive and the signal-dependent methods yielded good results. We then tested these two transformations in terms of robustness and selectivity
  • Keywords
    Fourier transforms; Wigner distribution; autoregressive processes; electromyography; exponential distribution; medical signal processing; time-frequency analysis; tracking; autoregressive spectra; classical method; cone shaped kernel distributions; exponential kernel distributions; robustness; selectivity; short time Fourier transform; signal-dependent method; simulation; smooth pseudo Wigner Ville; synthetic uterine EMG signals; time/frequency distributions; tracking; Electric variables measurement; Electromyography; Filtering; Frequency; Kernel; Low pass filters; Position measurement; Shape measurement; Signal analysis; Signal design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Time-Frequency and Time-Scale Analysis, 1994., Proceedings of the IEEE-SP International Symposium on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    0-7803-2127-8
  • Type

    conf

  • DOI
    10.1109/TFSA.1994.467287
  • Filename
    467287