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A system for heart sounds classification.

Redlarski G, Gradolewski D, Palkowski A - PLoS ONE (2014)

Bottom Line: The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods.Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue.The respective system is compared with four different major classification methods, proving its reliability.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechatronics and High Voltage Engineering, Gdansk University of Technology, Gdansk, Poland.

ABSTRACT
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases - one of the major causes of death around the globe - a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However, appropriate algorithms for auto-diagnosis systems of heart diseases that could be capable of distinguishing most of known pathological states have not been yet developed. The main issue is non-stationary character of phonocardiography signals as well as a wide range of distinguishable pathological heart sounds. In this paper a new heart sound classification technique, which might find use in medical diagnostic systems, is presented. It is shown that by combining Linear Predictive Coding coefficients, used for future extraction, with a classifier built upon combining Support Vector Machine and Modified Cuckoo Search algorithm, an improvement in performance of the diagnostic system, in terms of accuracy, complexity and range of distinguishable heart sounds, can be made. The developed system achieved accuracy above 93% for all considered cases including simultaneous identification of twelve different heart sound classes. The respective system is compared with four different major classification methods, proving its reliability.

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Related in: MedlinePlus

A S3 heart tone and LPC filter spectra.A comparison between a real S3 heart tone spectrum and spectra of filters estimated by the LPC algorithm. The 24th order filter provides the closest representation of the original heart tone spectrum.
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pone-0112673-g003: A S3 heart tone and LPC filter spectra.A comparison between a real S3 heart tone spectrum and spectra of filters estimated by the LPC algorithm. The 24th order filter provides the closest representation of the original heart tone spectrum.

Mentions: Due to differences in dynamics of speech and heart sounds, in order to properly identify the recorded signals, it is necessary to change the order of the filter describing the signal spectrum. Assuming that there could be additional peaks in the case of cardiac pathologies, in order to map the spectrum at least nine transmittance poles are needed. To ensure real coefficients of the polynomial, it is necessary to couple the poles in pairs, which requires at least an 18th order transmittance [18]. Figure 3 presents that by the use of a 24th order transmittance even a better spectrum matching is reached. Finally, the transfer function of the filter may be written as:(2)


A system for heart sounds classification.

Redlarski G, Gradolewski D, Palkowski A - PLoS ONE (2014)

A S3 heart tone and LPC filter spectra.A comparison between a real S3 heart tone spectrum and spectra of filters estimated by the LPC algorithm. The 24th order filter provides the closest representation of the original heart tone spectrum.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231067&req=5

pone-0112673-g003: A S3 heart tone and LPC filter spectra.A comparison between a real S3 heart tone spectrum and spectra of filters estimated by the LPC algorithm. The 24th order filter provides the closest representation of the original heart tone spectrum.
Mentions: Due to differences in dynamics of speech and heart sounds, in order to properly identify the recorded signals, it is necessary to change the order of the filter describing the signal spectrum. Assuming that there could be additional peaks in the case of cardiac pathologies, in order to map the spectrum at least nine transmittance poles are needed. To ensure real coefficients of the polynomial, it is necessary to couple the poles in pairs, which requires at least an 18th order transmittance [18]. Figure 3 presents that by the use of a 24th order transmittance even a better spectrum matching is reached. Finally, the transfer function of the filter may be written as:(2)

Bottom Line: The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods.Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue.The respective system is compared with four different major classification methods, proving its reliability.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechatronics and High Voltage Engineering, Gdansk University of Technology, Gdansk, Poland.

ABSTRACT
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases - one of the major causes of death around the globe - a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However, appropriate algorithms for auto-diagnosis systems of heart diseases that could be capable of distinguishing most of known pathological states have not been yet developed. The main issue is non-stationary character of phonocardiography signals as well as a wide range of distinguishable pathological heart sounds. In this paper a new heart sound classification technique, which might find use in medical diagnostic systems, is presented. It is shown that by combining Linear Predictive Coding coefficients, used for future extraction, with a classifier built upon combining Support Vector Machine and Modified Cuckoo Search algorithm, an improvement in performance of the diagnostic system, in terms of accuracy, complexity and range of distinguishable heart sounds, can be made. The developed system achieved accuracy above 93% for all considered cases including simultaneous identification of twelve different heart sound classes. The respective system is compared with four different major classification methods, proving its reliability.

Show MeSH
Related in: MedlinePlus