Signal Processing Tools for Heart Sounds Analysis Based on Time-Frequency Domain
Ali Moukadem
MIPS Laboratory, University of Haute Alsace, 68093 Mulhouse, France
Christian Brandt
Center of Clinical Investigations, University Hospital of Strasbourg, Inserm, BP 426, 67091 Strasbourg, France
Emmanuel Andrès *
Department of Internal Medicine, University Hospital of Strasbourg, BP 426, 67091 Strasbourg, France
Samy Talha
Laboratory of Physiology and Functional Explorations, University Hospital of Strasbourg, BP 426, 67091 Strasbourg, France
Alain Dieterlen
MIPS Laboratory, University of Haute Alsace, 68093 Mulhouse, France
*Author to whom correspondence should be addressed.
Abstract
This paper present several signal processing tools for the analysis of heart sounds. Cardiac auscultation is noninvasive, low-cost and accurate to diagnose some heart diseases. A new module for the segmentation of heart sounds based on S-Transform is presented. The heart sound segmentation process divides the Phono Cardio Gram (PCG) signal into four parts: S1 (first heart sound), systole, S2 (second heart sound) and diastole. The segmentation can be considered one of the most important phases in the auto-analysis of PCG signals. A segmentation method based on the Shannon energy of the local spectrum calculated by the S-transform is proposed. Then, the energy concentration of the S-transform is optimized to accurately detect the boundaries of the localized sounds. New features based on the energy concentration of the S-transform are proposed to classify S1 and S2 and other features based on the complexity measure via Time-Frequency (TF) domain are proposed to detect systolic murmurs.
Keywords: Heart sounds, segmentation, feature extraction, classification