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一种先天性心脏病杂音分割及分析方法

A heart murmur segmentation and analysis method for congenital heart disease

作者: 房玉  江钟伟  王海滨  陶婷 
单位:<span style="font-family:宋体">日本山口大学创成科学研究科(日本山口县宇部市</span>755-8611<span style="font-family:宋体">)</span><p><span style="font-family:宋体">西华大学电气与电子信息学院(中国成都</span> 610039<span style="font-family:宋体">)</span></p>
关键词: 心音;  先天性心脏病;  梅尔尺度特征参数;  频率切片小波变换;  特征矩波形 
分类号:R318.04
出版年·卷·期(页码):2018·37·2(151-156)
摘要:

目的 心音信号中的杂音成分可以反映心脏结构缺损等异常情况。本文提出一种心杂音分割及分析方法用于先心病杂音信号的识别。方法 为去除临床采集心音信号中的噪声干扰, 采用基于频率切片小波变换的降噪新方法提高听诊精度。然后采用特征矩波形分析方法分割并提取心脏杂音间期信号。最后对心脏杂音间期心音信号提取心音梅尔尺度特征参数。结果 通过临床采集的32例正常和16例室间隔缺损心音数据进行实验, 计算心脏杂音间期片段提取特征参数的平均值和标准差, 得到正常及室间隔缺损患儿心音数据的梅尔尺度特征参数范围。结论 该方法可以在心脏收缩杂音期有效识别室间隔缺损心音信号特征, 对于舒张杂音期信号尚需进行多角度特征提取及分析。该方法可以为典型先心病筛查及监控提供有效参考。

Objective Heart murmur of heart sounds can reflect the abnormal defects of the heart structure. A heart sound segmentation and analysis method is proposed for heart murmur identification of congenital heart disease. Methods At first, a novel noise reduction method based on frequency slice wavelet transform (FSWT) is applied to remove the surrounding noise. And then the duration of heart murmur is segmented and extracted by the characteristic moment waveform. Finally, the Mel-scale frequency features are extracted based on Mel frequency cepstrum coefficients for the heart murmur signal. Results The heart sound data including 32 normal cases and 16 ventricular septal defect (VSD) cases are applied to validate the efficiency of the proposed method. And the parameter scopes of normal and VSD data are calculated by the average values and standard deviations of the Mel-scale features. Conclusions The proposed method can identify the characteristic of VSD heart sounds in the duration of systolic murmurs. And more features may be extracted from diastolic murmurs for further analysis. The proposed method can be the effective reference for the screening and monitoring of typical congenital heart disease.

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