生物医学工程研究2024，Vol.43Issue(5)：369-376,8.DOI:10.19529/j.cnki.1672-6278.2024.05.04
基于改进残差网络的心脏杂音检测方法
A heart murmur detection method based on improved residual network
摘要
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.关键词
心血管疾病/心脏杂音/杂音检测/对数梅尔谱/注意力机制/残差神经网络Key words
Cardiovascular disease/Heart murmurs/Murmur detection/Log-Mel spectrogram/Attention mechanisms/Residual neural networks分类
医药卫生引用本文复制引用
李世龙,何培宇,黄昭涵,李莉,赵启军,潘帆..基于改进残差网络的心脏杂音检测方法[J].生物医学工程研究,2024,43(5):369-376,8.基金项目
国家自然科学基金项目(62066042) （62066042）
四川省重点研发项目(2022YFG0045) （2022YFG0045）
中央高校基本科研业务费专项资金(2022SCU12008). （2022SCU12008）
