Wavelet based fractal method in early human development

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.