Acoustic cardiac signals analysis: a Kalman filter–based approach

Acoustic cardiac signals analysis: a Kalman filter–based approach

Sheik Hussain Salleh,1 Hadrina Sheik Hussain,2 Tan Tian Swee,2 Chee-Ming Ting,2 Alias Mohd Noor,2 Surasak Pipatsart,3 Jalil Ali,4 Preecha P Yupapin31Department of Biomedical Instrumentation and Signal Processing, Universiti Teknologi Malaysia, Skudai, Malaysia; 2Centre for Biomedical Engineering Tra...

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Autores principales: Salleh SH, Hussain HS, Swee TT, Ting CM, Noor AM, Pipatsart S, Ali J, Yupapin PP
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2012
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Medicine (General)
R5-920
Acceso en línea:https://doaj.org/article/095e699623dc46a181fdd7e72e9cb1b7
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spelling oai:doaj.org-article:095e699623dc46a181fdd7e72e9cb1b72021-12-02T07:22:59ZAcoustic cardiac signals analysis: a Kalman filter–based approach1176-91141178-2013https://doaj.org/article/095e699623dc46a181fdd7e72e9cb1b72012-06-01T00:00:00Zhttp://www.dovepress.com/acoustic-cardiac-signals-analysis-a-kalman-filterndashbased-approach-a10077https://doaj.org/toc/1176-9114https://doaj.org/toc/1178-2013Sheik Hussain Salleh,1 Hadrina Sheik Hussain,2 Tan Tian Swee,2 Chee-Ming Ting,2 Alias Mohd Noor,2 Surasak Pipatsart,3 Jalil Ali,4 Preecha P Yupapin31Department of Biomedical Instrumentation and Signal Processing, Universiti Teknologi Malaysia, Skudai, Malaysia; 2Centre for Biomedical Engineering Transportation Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; 3Nanoscale Science and Engineering Research Alliance, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Institute of Advanced Photonics Science, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAbstract: Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss–Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.Keywords: heart sound, murmurs, ECG, Kalman filters, acoustic cardiac signalsSalleh SHHussain HSSwee TTTing CMNoor AMPipatsart SAli JYupapin PPDove Medical PressarticleMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol 2012, Iss default, Pp 2873-2881 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine (General)
R5-920
spellingShingle Medicine (General)
R5-920
Salleh SH
Hussain HS
Swee TT
Ting CM
Noor AM
Pipatsart S
Ali J
Yupapin PP
Acoustic cardiac signals analysis: a Kalman filter–based approach
description Sheik Hussain Salleh,1 Hadrina Sheik Hussain,2 Tan Tian Swee,2 Chee-Ming Ting,2 Alias Mohd Noor,2 Surasak Pipatsart,3 Jalil Ali,4 Preecha P Yupapin31Department of Biomedical Instrumentation and Signal Processing, Universiti Teknologi Malaysia, Skudai, Malaysia; 2Centre for Biomedical Engineering Transportation Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; 3Nanoscale Science and Engineering Research Alliance, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Institute of Advanced Photonics Science, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAbstract: Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss–Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.Keywords: heart sound, murmurs, ECG, Kalman filters, acoustic cardiac signals
format article
author Salleh SH
Hussain HS
Swee TT
Ting CM
Noor AM
Pipatsart S
Ali J
Yupapin PP
author_facet Salleh SH
Hussain HS
Swee TT
Ting CM
Noor AM
Pipatsart S
Ali J
Yupapin PP
author_sort Salleh SH
title Acoustic cardiac signals analysis: a Kalman filter–based approach
title_short Acoustic cardiac signals analysis: a Kalman filter–based approach
title_full Acoustic cardiac signals analysis: a Kalman filter–based approach
title_fullStr Acoustic cardiac signals analysis: a Kalman filter–based approach
title_full_unstemmed Acoustic cardiac signals analysis: a Kalman filter–based approach
title_sort acoustic cardiac signals analysis: a kalman filter–based approach
publisher Dove Medical Press
publishDate 2012
url https://doaj.org/article/095e699623dc46a181fdd7e72e9cb1b7
work_keys_str_mv AT sallehsh acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
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AT sweett acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
AT tingcm acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
AT nooram acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
AT pipatsarts acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
AT alij acousticcardiacsignalsanalysisakalmanfilterampndashbasedapproach
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