Detection and identification of heart sounds using homomorphic envelogram and self-organizing probabilistic model

D. Gill*, N. Gavrieli, N. Intrator

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

85 Scopus citations

Abstract

This work presents a novel method for automatic detection and identification of heart sounds. Homomorphic filtering is used to obtain a smooth envelogram of the phonocardiogram, which enables a robust detection of events of interest in heart sound signal. Sequences of features extracted from the detected events are used as observations of a hidden Markov model. It is demonstrated that the task of detection and identification of the major heart sounds can be learned from unlabelled phonocardiograms by an unsupervised training process and without the assistance of any additional synchronizing channels.

Original languageEnglish
Title of host publicationComputers in Cardiology, 2005
Pages957-960
Number of pages4
DOIs
StatePublished - 2005
EventComputers in Cardiology, 2005 - Lyon, France
Duration: 25 Sep 200528 Sep 2005

Publication series

NameComputers in Cardiology
Volume32
ISSN (Print)0276-6574

Conference

ConferenceComputers in Cardiology, 2005
Country/TerritoryFrance
CityLyon
Period25/09/0528/09/05

Fingerprint

Dive into the research topics of 'Detection and identification of heart sounds using homomorphic envelogram and self-organizing probabilistic model'. Together they form a unique fingerprint.

Cite this