A heart murmur detection method based on improved residual network
LI Shilong
HE Peiyu
HUANG Zhaohan
LI Li
ZHAO Qijun
PAN Fan
Abstract：In view of the fact that there is no recognition method for systolic and diastolic murmurs of heart sounds,we proposed a murmur detection method based on improved residual network to determine whether a heart murmur exists in a patient by detecting sys-tolic and diastolic murmurs in multiple auscultation zones.Firstly,the heart sound data were segmented into heart sound signal seg-ments according to the heart sound time phase.Then,the log-Mel spectral features of the heart sound segment samples were extracted.Finally,the residual neural network model embedded in the channel attention mechanism was used to detect heart murmurs.We per-formed 5 cross-validation on the CirCor Digiscope dataset 2022,and the average accuracy,average recall,average precision and aver-age F1 score of heart murmur detection reached 90.05%,63.74%,84.20%and 72.28%,respectively.The experimental results show that the proposed method has a good accuracy in detecting noise based on time-phase cut heart sound data,and can provide an impor-tant basis for automatic analysis of cardiovascular diseases.
Keywords：Cardiovascular diseaseHeart murmursMurmur detectionLog-Mel spectrogramAttention mechanismsResidual neural networks
Publication Date：2024-10-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：8( 369-376 )