Detecting fetal heart sounds by means of Fractal Dimension analysis in the Wavelet domain

A Fractal Dimension and Empirical Mode Decomposition-Based Method for Protein Sequence Analysis

In bioinformatics, the biological functions of proteins and their interactions can often be analyzed by the similarity of their sequences. In this paper, the authors combine the fractal dimension, empirical mode decomposition (EMD), and sliding window for protein sequence comparison. First, the protein sequence is characterized and digitized into a signal, and then the signal characteristics are obtained by using EMD and fractal dimension. Each protein sequence can be decomposed into Intrinsic Mode Functions (IMFs). The fixed window’s fractal dimension is applied to each IMF and the original signal to extract the protein sequence characteristics. Experiments have shown that the feature extracted by this hybrid method is superior to the EMD method alone.

AcCorps: A low-cost 3D printed stethoscope for fetal phonocardiography

The analysis of fetal heart rate provides valuable information regarding the fetus wellbeing. Fetal phonocardiography is a low-cost and passive method allowing the acquisition of fetal heart rate by recording acoustic vibrations on the mother's abdomen. However, most of available stethoscopes are not optimized for a robust acquisition of fetal heart sound. In this publication, we investigated a new design of low-cost and 3D printed stethoscope. This device was optimized to provide an acoustic amplification especially in the low-frequency band which corresponds to the fetal heart sounds. This device was tested i) in silico, ii) on a test bench and iii) on 5 pregnant volunteers.