改进变值逻辑与线性预测在心音分类中的应用  

Application of improved variable logic and linear prediction in the classification of heart sounds

作　　者：王彦麟 孙静[1] 杨宏波 郭涛 潘家华 王威廉[1] WANG Yanlin;SUN Jing;YANG Hongbo;GUO Tao;PAN Jiahua;WANG Weilian(School of Information Science&Engineering,Yunnan University,Kunming 650500,Yunnan,China;Fuwai Yunnan Cardiovascular Hospital,Kunming 650102,Yunnan,China)

机构地区：[1]云南大学信息学院,云南昆明650500 [2]云南省阜外心血管病医院,云南昆明650102

出　　处：《云南大学学报（自然科学版）》2024年第3期432-442,共11页Journal of Yunnan University(Natural Sciences Edition)

基　　金：国家自然科学基金(81960067);云南省重大科技专项(2018ZF017)。

摘　　要：心音对于评价心脏健康状况具有重要作用.文章介绍了一种新的基于变值逻辑与线性预测倒谱系数融合特征的先心病分类算法,有助于提取心音中的深度病理特征.算法首先对心音进行降噪、包络提取;然后进行变值逻辑运算、标记并转换为可分析的测度数据,并计算信号的线性预测倒谱系数进行特征融合;最后使用随机森林,XGBOOST和LIGHTGBM机器学习分类器进行先心病二分类.研究所用心音样本共4000例,测试结果对正常和异常心音分类的平均准确率为0.9138.算法无需对心音进行心动周期分割,大大简化了分析流程,可望用于先心病的筛查.Heart sounds play a vital role in assessing cardiac health.This article introduces a novel congenital heart disease classification algorithm based on the fusion of features utilizing variable logic and linear predictive cepstral coefficients.This approach aids in the extraction of profound pathological characteristics from heart sounds.The algorithm begins by denoising and extracting envelopes from the heart sounds.It then proceeds to perform variable logic operations,labels,and transforms the data into analyzable measurement data.Furthermore,it calculates the linear predictive cepstral coefficients of the signal for feature fusion.Finally,a binary classification of congenital heart disease is conducted using machine learning classifiers,specifically random forest(RF),XGBOOST and LIGHTGBM.The study utilized a total of 4000 heart sound samples,resulting in an average accuracy of 0.9138 in distinguishing between normal and abnormal heart sounds.Importantly,this algorithm eliminates the need for segmenting heart sounds by cardiac cycles,significantly streamlining the analysis process,and holds promise for congenital heart disease screening.

关 键 词：心音 先心病 3比特编码变值逻辑 线性预测倒谱系数 特征融合 

分 类 号：TN912[电子电信—通信与信息系统]