Heart valve abnormality analysis method, system and device based on convolutional neural network

Abstract

An embodiment of the invention provides a heart valve abnormality analysis method based on a convolutional neural network. The method comprises the steps of segmenting a collected heart sound, and calculating a time-frequency spectrum of each heart sound segment; inputting the time-frequency spectrum of each heart sound segment into the convolutional neural network, and outputting a first result that the heart sound is normal or abnormal; extracting envelope spectrum characteristics and power spectrum characteristics of the heart sound with the first result that the heart sound is abnormal, inputting a logistic regression hidden semi-Markov model for segmentation, and outputting K states to which all frames in a cardiac cycle of the heart sound belong, wherein K is a natural number; extracting an energy feature of each state of the heart sound; and inputting the energy features into a support vector machine to obtain analysis results of aortic valve stenosis and / or aortic valve regurgitation and mitral valve stenosis and / or mitral valve regurgitation. According to the method, the heart valve abnormality is subjected to two-stage analysis, so that the accuracy of heart valve abnormality judgment can be improved, and the misdiagnosis risk is reduced.

Description

technical field [0001] The present application relates to the field of deep learning technology, in particular to a method, system and device for abnormal heart valve analysis based on convolutional neural network. Background technique [0002] Cardiac valve abnormalities are a common type of cardiovascular abnormalities, mainly including aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation and tricuspid regurgitation. Heart sound is a relatively easy to collect human physiological signal, which can reflect the health status of heart valves. Using heart sounds to analyze heart valve abnormalities has the advantages of low cost and easy promotion. [0003] The analysis of heart valve abnormalities based on traditional mechanical stethoscopes mainly relies on the experience of doctors, and it is difficult for ordinary residents to self-examine. Along with the invention and popularization of electronic stethoscope, researchers begin to use computer to ...

AI Technical Summary

Problems solved by technology

[0004] The purpose of this application is to overcome the existing problems of low accuracy and undispersed risk of misdiagnosis in the analysis of abnormal heart valves by using heart sounds and adopting one-time classification

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