Multi parametric classification of cardiovascular sounds

Abstract

The present application relates to a method for classifying a cardiovascular sound recorded from a living subject. The method comprises the step of extracting at least two signal parameters (309) from said cardiovascular sound, said at least two signal parameters characterizes at least two different properties of at least a part of said cardiovascular sound. The method further comprises the step of classifying said cardiovascular sound using said at least two signal parameters in a multivariate classification method (310). Furthermore, the application relates to a system, stethoscope and server for classifying a cardiovascular sound recorded from a living subject, where the above-described method has been implemented.

Description

FIELD OF THE INVENTION[0001]The present invention relates to methods and systems for classification of heart sounds recorded from a living subject into classes describing whether or not murmurs due to coronary artery stenosis is present in the heart sound.BACKGROUND OF THE INVENTION[0002]Coronary artery disease is the single most common cause of death from cardiovascular disease in the western world. The heart muscle receives its blood supply through the coronary arteries, and atherosclerosis is the most common pathophysiologic process occurring in the coronary arteries giving rise to coronary artery disease (CAD). Atherosclerosis is a process that builds up plaques within the artery, and the blood flow can therefore be is reduced or even blocked by the plaque. The constantly working heart requires a continuous and efficient blood supply in order to work properly. Defects in the blood supply may be very severe and even fatal. Increasing degrees of luminal diameter reduction or steno...

AI Technical Summary

Benefits of technology

[0008]Hereby a simple method for classifying cardiovascular sounds is achieved and the method is furthermore very robust since different properties of the cardiovascular sound is taken into account and used in a multivariate classification method. The cardiovascular sound related to turbulence consists of at least two components: a broad band component caused by turbulent blood flow colliding with the arterial wall and a narrow banded component related to the resonance frequency of the artery wall, therefore different variables describing different properties are needed in order to perform a robust classification. The different properties describe different characteristics of the cardiovascular sound and would therefore be uncorrelated and therefore provide different information of the cardiovascular sound. Different properties could for instance be the time duration of the diastolic segment of cardiovascular sound, the time duration of the systolic cardiovascular sound, the most dominant frequency component of the sound, the bandwidth of different frequency components, the energy in two frequency bands, the mobility of part of the signal, the complexity of the signal, the power ratio between different parts of the signal, e.g. two different segments or two different frequency bands, morphological characteristics such as correlation ratios between different segments or amplitude change over time. The method could easily be implemented in any kind of data processor unit and therefore be e.g. integrated in a software program which clinicians and doctors could use in order to classify the cardiovascular sound. Furthermore, the method could be integrated in a digital stethoscope and the stethoscope could therefore be used in order to classify a patient's cardiovascular sound. Since doctors and other clinicians are familiar with a stethoscope, they could easily be taught to use the stethoscope to classify the cardiovascular sound. The result is that the classification could assist the doctor or other clinicians to diagnose whether or not the patient suffers from CAD.

[0030]The invention further relates to a computer-readable medium having stored therein instructions for causing a processing unit to execute a method as described above. Hereby the same advantages as described above are achieved.

Problems solved by technology

Defects in the blood supply may be very severe and even fatal.

However, the above-mentioned techniques are all rather complicated and expensive to use and therefore only patients with specific symptoms are offered such examinations.

Using these conventional techniques, it is difficult to provide an automated device for diagnosis of coronary stenosis using auscultatory sounds.

Moreover, it is often difficult to implement the conventional techniques in a manner that may be applied in real-time or pseudo real-time to aid the clinician.

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