Heart murmur detection/classification using cochlea-like pre-processing and artificial intelligence

W. Ahmad, M. I. Hayee, J. L. Fitzakerley, S. Burns, G. Nordehn

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this research paper, we used a novel approach to pre-process the heart sound signals by altering the electrical signal in a similar way as is done by human cochlea before they go to Artificial Intelligence (AI) for murmur detection/classification. Cochlea-like pre-processing changes the spectral contents of the heart sounds to enhance the murmur information which can then be detected/classified more accurately by AI circuitry. We designed a heart murmur detection/classification system based upon this approach and tested this system using simulated sounds of various murmur types. Our test results show that this approach significantly improves heart murmur detection/classification accuracy.

Original languageEnglish (US)
Pages (from-to)87-96
Number of pages10
JournalInternational Journal of Biomedical Engineering and Technology
Volume7
Issue number1
DOIs
StatePublished - Dec 12 2011

Fingerprint

Artificial intelligence
Acoustic waves
Processing

Keywords

  • AI
  • ANN
  • Artificial intelligence
  • Artificial neural network
  • CLPP
  • Cochlea-like pre-processing
  • Detection/classification
  • Heart murmurs
  • Human cochlea

Cite this

@article{809bc6ee2dd74dd186910cd1f1b8b85b,
title = "Heart murmur detection/classification using cochlea-like pre-processing and artificial intelligence",
abstract = "In this research paper, we used a novel approach to pre-process the heart sound signals by altering the electrical signal in a similar way as is done by human cochlea before they go to Artificial Intelligence (AI) for murmur detection/classification. Cochlea-like pre-processing changes the spectral contents of the heart sounds to enhance the murmur information which can then be detected/classified more accurately by AI circuitry. We designed a heart murmur detection/classification system based upon this approach and tested this system using simulated sounds of various murmur types. Our test results show that this approach significantly improves heart murmur detection/classification accuracy.",
keywords = "AI, ANN, Artificial intelligence, Artificial neural network, CLPP, Cochlea-like pre-processing, Detection/classification, Heart murmurs, Human cochlea",
author = "W. Ahmad and Hayee, {M. I.} and Fitzakerley, {J. L.} and S. Burns and G. Nordehn",
year = "2011",
month = "12",
day = "12",
doi = "10.1504/IJBET.2011.042500",
language = "English (US)",
volume = "7",
pages = "87--96",
journal = "International Journal of Biomedical Engineering and Technology",
issn = "1752-6418",
publisher = "Inderscience Enterprises Ltd",
number = "1",

}

TY - JOUR

T1 - Heart murmur detection/classification using cochlea-like pre-processing and artificial intelligence

AU - Ahmad, W.

AU - Hayee, M. I.

AU - Fitzakerley, J. L.

AU - Burns, S.

AU - Nordehn, G.

PY - 2011/12/12

Y1 - 2011/12/12

N2 - In this research paper, we used a novel approach to pre-process the heart sound signals by altering the electrical signal in a similar way as is done by human cochlea before they go to Artificial Intelligence (AI) for murmur detection/classification. Cochlea-like pre-processing changes the spectral contents of the heart sounds to enhance the murmur information which can then be detected/classified more accurately by AI circuitry. We designed a heart murmur detection/classification system based upon this approach and tested this system using simulated sounds of various murmur types. Our test results show that this approach significantly improves heart murmur detection/classification accuracy.

AB - In this research paper, we used a novel approach to pre-process the heart sound signals by altering the electrical signal in a similar way as is done by human cochlea before they go to Artificial Intelligence (AI) for murmur detection/classification. Cochlea-like pre-processing changes the spectral contents of the heart sounds to enhance the murmur information which can then be detected/classified more accurately by AI circuitry. We designed a heart murmur detection/classification system based upon this approach and tested this system using simulated sounds of various murmur types. Our test results show that this approach significantly improves heart murmur detection/classification accuracy.

KW - AI

KW - ANN

KW - Artificial intelligence

KW - Artificial neural network

KW - CLPP

KW - Cochlea-like pre-processing

KW - Detection/classification

KW - Heart murmurs

KW - Human cochlea

UR - http://www.scopus.com/inward/record.url?scp=82955192494&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=82955192494&partnerID=8YFLogxK

U2 - 10.1504/IJBET.2011.042500

DO - 10.1504/IJBET.2011.042500

M3 - Article

VL - 7

SP - 87

EP - 96

JO - International Journal of Biomedical Engineering and Technology

JF - International Journal of Biomedical Engineering and Technology

SN - 1752-6418

IS - 1

ER -