摘要
心音信号分析在无创诊断心血管疾病中发挥着重要作用,病灶心音信号中包含大量的心脏疾病信息。本文根据心音信号频率分布的特点,采用小波变换算法,在不同的尺度上对心音信号进行提取分析,将不同尺度的高频部分进行重构,分别计算其能量,再对比正常心音在相应尺度上的能量分布,通过仿真可实现对病灶信号的识别。本文方法能够准确识别病灶信号,由于较少采用复杂度高的算法方法,因而具有较高的检测效率。
Analysis of heart sound plays an important role in the non-invasive diagnosis of cardiovascular diseases. The lesions heart sound contains a lot of information about heart diseases. According to the characteristics of frequency distribution of heart sound signals, this paper adopts wavelet transform algorithm to extract and analyse heart sound signals at different sizes, reconstructs the high frequency of heart sound, and calculates the energy separately, contrasts with energy distribution of the normal heart sound in corresponding sizes, achieves the recognition of lesion heart sound by emulation. This method which merely uses highly complicated algorithm could recognize the lesions heart sound signals, and has higher detection efficiency
出处
《中国医疗设备》
2013年第2期9-12,共4页
China Medical Devices
基金
中央高校基本科研业务经费资助项目(k50510020034)
关键词
小波变换
心音信号
特征提取
小波能量
wavelet transform
heart sound
feature extraction
wavelet energy
