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.
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.
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