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
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