Limits...
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.

Show MeSH

Related in: MedlinePlus

Result of the heart tone segmentation algorithm.The waveform presented contains normal S1, S2 and S3 heart sounds, which are segmented by a variable size time window for further analysis.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4231067&req=5

pone-0112673-g002: Result of the heart tone segmentation algorithm.The waveform presented contains normal S1, S2 and S3 heart sounds, which are segmented by a variable size time window for further analysis.

Mentions: Heart sounds are characterized by a large variation in both time and frequency domains. Therefore, the PCG signals – like most biological signals – are classified as non-stationary. Thus, it is strictly inadvisable to divide PCG signals using a fixed size time window, as it is used in the case of speech signal coding. For this reason a special algorithm was developed that separates each heart tone using a variable size time window. Figure 2 presents the result of the separation task. Each of these frames determine the parameters of the filter.


A system for heart sounds classification.

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

Result of the heart tone segmentation algorithm.The waveform presented contains normal S1, S2 and S3 heart sounds, which are segmented by a variable size time window for further analysis.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0112673-g002: Result of the heart tone segmentation algorithm.The waveform presented contains normal S1, S2 and S3 heart sounds, which are segmented by a variable size time window for further analysis.
Mentions: Heart sounds are characterized by a large variation in both time and frequency domains. Therefore, the PCG signals – like most biological signals – are classified as non-stationary. Thus, it is strictly inadvisable to divide PCG signals using a fixed size time window, as it is used in the case of speech signal coding. For this reason a special algorithm was developed that separates each heart tone using a variable size time window. Figure 2 presents the result of the separation task. Each of these frames determine the parameters of the filter.

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