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中国生物医学工程学报  2018, Vol. 37 Issue (5): 537-544    DOI: 10.3969/j.issn.0258-8021.2018.05.004
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心音特征在慢性心力衰竭分型辅助诊断中的应用研究
孙伟,郭兴明#*,郑伊能
(重庆大学生物工程学院,重庆市医疗电子技术工程研究中心,重庆 400044)
Application of Heart Sound Feature in the Typing Aided Diagnosis of Chronic Heart Failure
Sun Wei,Guo Xingming#*,Zheng Yineng
College of Bioengineering, Chongqing University, Chongqing Engineering Research Center for Medical Electronic Technology, Chongqing 400044, China)
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摘要 提取心音时域和时频域特征,比较分析射血分数降低型心衰(HFrEF)和射血分数保留型心衰(HFpEF)患者各特征之间的关系。共采集了72列HFrEF患者和172列HFpEF患者20分钟的心音数据,提取第一心音与第二心音时限之比(TS1/TS2)、第一心音与第二心音幅值之比(S1/S2)、舒张期时限与收缩期时限之比的总体标准差(SDDS)、S1间期总体标准差(SDSSI)等4个时域特征。S变换分析其时频域特性,提取第一心音能量与第二心音能量之比(ES1/ES2),低频能量分数(EF-LF)、高频能量分数(EF-HF)、收缩期低频能量分数(EF-SLF)和高频能量分数(EF-SHF)、舒张期低频能量分数(EF-DLF)和高频能量分数(EF-DHF)7个时频域特征,分别进行统计学分析和聚类分析。TS1/TS2、S1/S2、SDDS、SDSSI、ES1/ES2、EF-SLF、EF-DLF在两组间均有统计学差异(P<0.05);EF-LF、EF-HF、EF-SHF、EF-DHF无统计学意义(P>0.05)。选择其中4个相对独立的特征值进行聚类分析,区分HFrEF组和HFpEF组的灵敏性和特异性分别为93.06%和84.88%。提取的心音特征反映了两组信号的差异性,为心音信号在慢性心力衰竭分型辅助诊断中的应用提供了理论依据。
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孙伟
郭兴明
郑伊能
关键词 心音射血分数降低型心力衰竭射血分数保留型心力衰竭心衰分型诊断S变换    
Abstract:This article aimed to analyze the relationship between heart sound features extracted from time domain and time-frequency domain in heart failure patients with reduced ejection fraction (HFrEF) and heart failure patients with preserved ejection fraction (HFpEF). The heart sound signal lasting 20 minutes was recorded totally from the HFrEF patients(n=72)and HFpEF patients(n=172), the time ratio of the first to second heart sound(TS1/TS2), the amplitude ratio of the first to second heart sound(S1/S2), standard deviation of the ratio of diastolic to systolic duration(SDDS) and standard deviation of S1and S1interval (SDDSI) were extracted. Then S transformation was performed on the heart sound signal to analyze its characteristics in time-frequency domain, and the energy ratio of the first to second heart sound(ES1/ES2), the energy fraction of heart sound signal with low frequency(EF-LF), the energy fraction of heart sound signal with high frequency(EF-HF), the energy fraction of heart sound signal with low and high frequency in cardiac systole respectively(EF-SLF,EF-SHF), the energy fraction of heart sound signal with low and high frequency in cardiac diastole respectively(EF-DLF,EF-DHF) were extracted as well. Statistical results demonstrated that significant difference exited forTS1/TS2,S1/S2,SDDS,SDSSI,ES1/ES2,EF-SLF, and EF-DLF between two groups(P<0.05), while EF-LF,EF-HF,EF-SHF,and EF-DHF had no statisticcal significance(P>0.05). ISODATA was performed with four relatively independent features, the sensitivity and specificity for discriminating HFrEF patients and HFpEF patients reached 93.06% and 84.88% respectively. The features extracted from heart sound signal described the significant difference between two groups, which provided the basis of aided typing diagnosis for chronic heart failure.
Key wordsheart sound    heart failure with reduced ejection fraction(HFrEF)    heart failure with preserved ejection fraction(HFpEF)    typing diagnosis for heart failure    S transform
收稿日期: 2018-01-17     
PACS:  R318  
基金资助:国家自然科学基金(31570003)
通讯作者: guoxm@cqu.edu.cn   
引用本文:   
孙伟,郭兴明,郑伊能. 心音特征在慢性心力衰竭分型辅助诊断中的应用研究[J]. 中国生物医学工程学报, 2018, 37(5): 537-544.
Sun Wei,Guo Xingming,Zheng Yineng. Application of Heart Sound Feature in the Typing Aided Diagnosis of Chronic Heart Failure. Chinese Journal of Biomedical Engineering, 2018, 37(5): 537-544.
链接本文:  
http://cjbme.csbme.org/CN/10.3969/j.issn.0258-8021.2018.05.004     或     http://cjbme.csbme.org/CN/Y2018/V37/I5/537
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