Classification of four types of common murmurs using wavelets and a learning vector quantization network

F. Rios-Gutiérrez, R. Alba-Flores, K. Ejaz, G. Nordehn, N. Andrisevic, Stanley G Burns

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

In this work we present the development of a system that can be used for the study, detection and classification of human heart sounds using digital signal processing and artificial intelligence techniques. The design and implementation of such system is broken down into two processes: digital signal processing part and artificial intelligence part. The ultimate goal of the project is to develop an intelligent system that can be used for the detection and classification of various types of human heart murmurs.

Original languageEnglish (US)
Title of host publicationInternational Joint Conference on Neural Networks 2006, IJCNN '06
Pages2206-2213
Number of pages8
StatePublished - Dec 1 2006
EventInternational Joint Conference on Neural Networks 2006, IJCNN '06 - Vancouver, BC, Canada
Duration: Jul 16 2006Jul 21 2006

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)1098-7576

Other

OtherInternational Joint Conference on Neural Networks 2006, IJCNN '06
CountryCanada
CityVancouver, BC
Period7/16/067/21/06

Fingerprint Dive into the research topics of 'Classification of four types of common murmurs using wavelets and a learning vector quantization network'. Together they form a unique fingerprint.

Cite this