基于非平稳系统辨识的心音包络自适应分割  

Adaptive Envelope Segmentation of Heart Sound Based on Non-Stationary System Identification

作　　者：许春冬[1] 周静 应冬文 龙清华[1] XU Chundong;ZHOU Jing;YING Dongwen;LONG Qinghua(School of Information Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China;Key Laboratory of Language Acoustics and Content Understanding,Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]江西理工大学信息工程学院,江西赣州341000 [2]中国科学院声学研究所,语言声学与内容理解重点实验室,北京100190

出　　处：《计算机工程》2020年第8期290-296,304,共8页Computer Engineering

基　　金：国家自然科学基金(11864016,11704164);国家级大学生创新创业训练计划项目(201810407019);江西省文化艺术科学规划项目(YG2017384);江西省研究生创新项目(YC2018-S330)。

摘　　要：为实现心音信号的有效分割,提出一种基于非平稳系统辨识的心音信号特征包络自适应分割方法。根据非平稳系统辨识原理,提取心音信号特征包络并对包络作平滑与展宽处理。基于重尺度小波降噪信噪比与特征包络均值参数,创建自适应阈值函数进行心音信号分割,同时利用包络与时域特征剔除因噪音及杂音引起的错误分割点。实验结果表明,该方法能够有效提取基础心音信号特征,分割精度达到89.21%,相比维奥拉积分包络分割法、改进型希尔伯特-黄变换包络双阈值分割法等对比方法分割精度更高、实时性更强。To effectively segment Heart Sound Signal(HSS),this paper proposes an adaptive segmentation method for heart sound based on Non-Stationary System Identification(NSSI),so as to extract the envelope of HSS,and smooth and broaden it.The method uses the noise reduction Signal to Noise Rate(SNR)of heavy-scale wavelet and the mean parameter of feature envelope to establish the adaptive threshold function for signal segmentation of heart sound.Also,the false segmentation points caused by noise and murmur are excluded according to the envelope and time domain features.Experimental results show that the proposed method can effectively extract the basic features of HSS,increasing the segmentation accuracy to 89.21%.Compared with the envelope segmentation method of Viola integral,improved double-threshold envelope segmentation method based on Hilbert-Huang transform and other methods,the proposed method has higher segmentation accuracy and real-time performance.

关 键 词：非平稳系统辨识 心音信号 心音分割 自适应阈值 包络提取 

分 类 号：TN912[电子电信—通信与信息系统]