MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM-BASED ABRUPT CHANGES DETECTION FOR HEART SOUNDS SEGMENTATION

Abstract

The aim of this paper is cardiac sound segmentation in order to extract significant clinical parameters that can aid cardiologists in diagnosis, through maximal overlap discrete wavelet transform (MODWT) and abrupt changes detection. After reconstruction of the fifth to seventh level of decomposition of the pre-processed phonocardiogram (PCG), we can correctly measure the time duration of Fundamental heart sounds (S1, S2), while the third and fourth levels localize murmurs and clicks. From this scope, it is possible to establish the time interval between clicks and fundamental heart sounds or evaluating murmur severity through energetic ratio. We have tested this approach on several phonocardiography records. Results show that this method performs greatly on long and short PCG records and gives the precise duration of fundamental heart sounds; we have achieved an accuracy of 88.6% in cardiac sounds segmentation.