[1]孙树平,吴越,黄婷婷,等.基于STMHT算法的心音分割研究[J].中国医学物理学杂志,2020,37(12):1553-1559.[doi:DOI:10.3969/j.issn.1005-202X.2020.12.016]
 SUN Shuping,WU Yue,HUANG Tingting,et al.STMHT-based heart sound segmentation[J].Chinese Journal of Medical Physics,2020,37(12):1553-1559.[doi:DOI:10.3969/j.issn.1005-202X.2020.12.016]
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基于STMHT算法的心音分割研究()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第12期
页码:
1553-1559
栏目:
医学信号处理与医学仪器
出版日期:
2020-12-30

文章信息/Info

Title:
STMHT-based heart sound segmentation
文章编号:
1005-202X(2020)12-1553-07
作者:
孙树平吴越黄婷婷张弼强杜小玉何沛光杨文博
南阳理工学院, 河南 南阳 473000
Author(s):
SUN Shuping WU Yue HUANG Tingting ZHANG Biqiang DU Xiaoyu HE Peiguang YANG Wenbo
Nanyang Institute of Technology, Nanyang 473000, China
关键词:
心音小波分解包络提取STMHT算法
Keywords:
heart sound wavelet decomposition envelope extraction short time modified Hilbert transform algorithm
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2020.12.016
文献标志码:
A
摘要:
第一心音(S1)和第二心音(S2)的定位和提取是利用心音分析诊断心脏病时的首要任务。鉴于此,本研究提出一种基于STMHT的心音分割法,分别提取S1和S2。本研究分为以下3个阶段:第一阶段,采用小波分解对心音信号进行预处理,保留心音信号的有效成分(21.5~689.0 Hz);第二阶段,用Viola积分波形法提取心音包络;最后,基于STMHT算法自动定位和提取S1和S2。对30例心音信号的提取结果进行评价,结果表明,S1和S2提取的准确率高达97.37%,优于其它已实现的有效方法。
Abstract:
When using heart sound analysis to diagnose heart diseases, the locations and extractions of the first heart sound (S1) and the second heart sound (S2) are primary task. Herein a heart sound segmentation method based on short-time modified Hilbert transform (STMHT) is proposed for separately extracting S1 and S2. The study is arranged as the following 3 stages. Wavelet decomposition is firstly employed to preprocess heart sound signals and remain the efficient component of heart sound signals (21.5-689.0 Hz), and then the envelope for heart sound signals is extracted using Viola integral waveform. Finally, S1 and S2 are automatically located and extracted by STMHT algorithm. The performance is evaluated by 30 cases of heart sound signals, and the results show that the accuracy of the S1 and S2 extraction is up to 97.37%, which is higher than that obtained by other methods.

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备注/Memo

备注/Memo:
【收稿日期】2020-04-23 【作者简介】孙树平,工学博士,研究方向:生物医学信号处理、模式识别,E-mail: Shuping.Sun@IEEE.org
更新日期/Last Update: 2020-12-30