• DocumentCode
    2387786
  • Title

    Wavelet based fractal method in early human development

  • Author

    Akay, Metin ; Mulder, Eduard J H

  • Author_Institution
    Rutgers Univ., Piscataway, NJ, USA
  • fYear
    1996
  • fDate
    18-21 Jun 1996
  • Firstpage
    93
  • Lastpage
    95
  • Abstract
    Fractal methods have found to be useful in characterizing biomedical signals. The use of fractal estimation requires the estimation of parameter H, which is directly related to the fractal dimension D. However, traditional fractal analysis requires that the biomedical signals be stationary. Here, the authors propose a novel approach which is a combination of the wavelet transform and fractal estimators to characterize the human fetal breathing signals. This study was performed on 26 fetuses. The variances of the wavelet coefficients were estimated at each scale. The slope of the representation on a logarithmic plot from the scales 5 to 1 was used to estimate the fractal dimension of the fetal breathing signals. The authors´ results suggested that fetal breathing rates have a rough structure
  • Keywords
    fractals; medical signal processing; wavelet transforms; biomedical signals characterization; early human development; fractal dimension; fractal estimation; human fetal breathing signals; logarithmic plot; rough structure; stationary biomedical signals; wavelet based fractal method; wavelet coefficients variances; Biological system modeling; Discrete wavelet transforms; Fractals; Frequency; Humans; Signal analysis; Signal processing; Statistics; Wavelet coefficients; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    0-7803-3512-0
  • Type

    conf

  • DOI
    10.1109/TFSA.1996.546694
  • Filename
    546694