Automatic heart sound analysis with short-time fourier transform and support vector machines

Wen Chung Kao; Chih Chao Wei; Jen Jui Liu; Pei Yung Hsiao

doi:10.1109/MWSCAS.2009.5236120

Automatic heart sound analysis with short-time fourier transform and support vector machines

Wen Chung Kao^*, Chih Chao Wei, Jen Jui Liu, Pei Yung Hsiao

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Citations (Scopus)

Abstract

Skilled cardiologists probe heart sounds by electronic stethoscope through human ears, but interpretation of heart sounds is a very special skill which is quite difficult to teach in a structured way. Because of this reason, automatic heart sound analysis in computer systems would be very helpful for medical staff. This paper presents a complete heart sound analysis system covering from the segmentation of beat cycles to the final determination of heart conditions. The kernels of heart beat cycle segmentation and recognition are based on autocorrelation, short-time Fourier transform, and support vector machines. The experiments are done by a public heart sound database released by Texas Heart Institute. A very promising recognition rate has been achieved.

Original language	English
Title of host publication	2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09
Pages	188-191
Number of pages	4
DOIs	https://doi.org/10.1109/MWSCAS.2009.5236120
Publication status	Published - 2009
Event	2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09 - Cancun, Mexico Duration: 2009 Aug 2 → 2009 Aug 5

Publication series

Name	Midwest Symposium on Circuits and Systems
ISSN (Print)	1548-3746

Other

Other	2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09
Country/Territory	Mexico
City	Cancun
Period	2009/08/02 → 2009/08/05

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/MWSCAS.2009.5236120

Cite this

Automatic heart sound analysis with short-time fourier transform and support vector machines. / Kao, Wen Chung; Wei, Chih Chao; Liu, Jen Jui et al.
2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09. 2009. p. 188-191 5236120 (Midwest Symposium on Circuits and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kao, WC, Wei, CC, Liu, JJ & Hsiao, PY 2009, Automatic heart sound analysis with short-time fourier transform and support vector machines. in 2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09., 5236120, Midwest Symposium on Circuits and Systems, pp. 188-191, 2009 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09, Cancun, Mexico, 2009/08/02. https://doi.org/10.1109/MWSCAS.2009.5236120

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abstract = "Skilled cardiologists probe heart sounds by electronic stethoscope through human ears, but interpretation of heart sounds is a very special skill which is quite difficult to teach in a structured way. Because of this reason, automatic heart sound analysis in computer systems would be very helpful for medical staff. This paper presents a complete heart sound analysis system covering from the segmentation of beat cycles to the final determination of heart conditions. The kernels of heart beat cycle segmentation and recognition are based on autocorrelation, short-time Fourier transform, and support vector machines. The experiments are done by a public heart sound database released by Texas Heart Institute. A very promising recognition rate has been achieved.",

author = "Kao, {Wen Chung} and Wei, {Chih Chao} and Liu, {Jen Jui} and Hsiao, {Pei Yung}",

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AB - Skilled cardiologists probe heart sounds by electronic stethoscope through human ears, but interpretation of heart sounds is a very special skill which is quite difficult to teach in a structured way. Because of this reason, automatic heart sound analysis in computer systems would be very helpful for medical staff. This paper presents a complete heart sound analysis system covering from the segmentation of beat cycles to the final determination of heart conditions. The kernels of heart beat cycle segmentation and recognition are based on autocorrelation, short-time Fourier transform, and support vector machines. The experiments are done by a public heart sound database released by Texas Heart Institute. A very promising recognition rate has been achieved.

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Automatic heart sound analysis with short-time fourier transform and support vector machines

Abstract

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