基于双谱特征提取和卷积神经网络的心音分类算法  

Heart sound classification algorithm based on bispectral feature extraction and convolutional neural networks

作　　者：彭利勇 全海燕 PENG Liyong;QUAN Haiyan(Department of Communication Engineering,Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,P.R.China)

机构地区：[1]昆明理工大学信息工程与自动化学院通信工程系,昆明650500

出　　处：《生物医学工程学杂志》2024年第5期977-985,994,共10页Journal of Biomedical Engineering

基　　金：国家自然科学基金项目(61861023)。

摘　　要：在全球的死亡案例中,心血管疾病(CVD)是主要的致死原因之一。心音分类识别在心血管疾病的早期发现中起着关键作用。正常心音和异常心音之间的区别并不明显,本文为提升心音分类模型的准确度,提出一种基于双谱分析的心音特征提取方法,并将其与卷积神经网络(CNN)结合,对心音进行分类。该算法能够有效地利用双谱分析来抑制高斯噪声,而且不需要准确分割心音信号就能提取其特征,同时结合了卷积神经网络的强大分类性能,从而实现对心音的准确分类。根据实验结果显示,在相同的数据和实验条件下,本文提出的算法在准确率、灵敏度和特异性方面分别达到了0.910、0.884和0.940。与其他心音分类算法相比,本文算法提升明显,并具有较强的鲁棒性和泛化能力,因此有望应用于先心病的辅助检测。Cardiovascular disease(CVD)is one of the leading causes of death worldwide.Heart sound classification plays a key role in the early detection of CVD.The difference between normal and abnormal heart sounds is not obvious.In this paper,in order to improve the accuracy of the heart sound classification model,we propose a heart sound feature extraction method based on bispectral analysis and combine it with convolutional neural network(CNN)to classify heart sounds.The model can effectively suppress Gaussian noise by using bispectral analysis and can effectively extract the features of heart sound signals without relying on the accurate segmentation of heart sound signals.At the same time,the model combines with the strong classification performance of convolutional neural network and finally achieves the accurate classification of heart sound.According to the experimental results,the proposed algorithm achieves 0.910,0.884 and 0.940 in terms of accuracy,sensitivity and specificity under the same data and experimental conditions,respectively.Compared with other heart sound classification algorithms,the proposed algorithm shows a significant improvement and strong robustness and generalization ability,so it is expected to be applied to the auxiliary detection of congenital heart disease.

关 键 词：心血管疾病 双谱分析 心音分类 卷积神经网络 

分 类 号：TN912.3[电子电信—通信与信息系统] TP183[电子电信—信息与通信工程] R540.4[自动化与计算机技术—控制理论与控制工程]