基于小波收缩的心音降噪最优化分析  

Optimization analysis of noise reduction in heart sound based on wavelet shrinkage

作　　者：余辉 姜博畅 刘雁飞 关红彦 

机构地区：[1]天津市生物医学检测技术及仪器重点实验室,天津300072 [2]天津天堰科技股份有限公司,天津300384

出　　处：《电子测量与仪器学报》2017年第3期383-388,共6页Journal of Electronic Measurement and Instrumentation

基　　金：国家重大仪器专项(2012YQ060165);天津市科技支撑重点项目(14ZCZDSF00005)资助

摘　　要：基于小波收缩技术提出一种最优化降噪方案用于去除心音信号噪声。依据频带相似匹配原则,分析心音信号频率特征和Haar、Daubechies、Symlets和Coiflets正交小波的特性,基于分析结果选取了Coif5小波并确定最优小波包进行分解重构。另外,提出一种光滑连续的自适应弹性阈值函数,能够克服硬阈值函数间断点问题,并基于4种阈值规则定量评价了其在不同信噪比下的降噪效果。仿真结果表明,当信噪比小于50 d B时,本优化方案配合启发式阈值规则能保留充足的心音细节信息,同时有效去除噪音。A denoising scheme based on wavelet shrinkage technique is proposed to remove the noise in the heart sound signal.Firstly,the characteristics of heart sound signal frequency were analyzed and Haar,Daubechies,Symlets and Coiflets orthogonal wavelets were studied for contrast in accordance with the principle of frequency band similarity matching.Based on the statistical results,Coif5 wavelet was chosen for the decomposition and reconstruction of heart sound signal.Besides,a smooth and continuous adaptive elastic threshold function was designed for wavelet shrinkage,which can overcome the problem of discontinuous hard threshold function.The noise reduction effects were compared under four threshold rules.The simulation results show that,when the SNR is less than 50 d B,the optimization scheme with Heursure threshold rule can retain sufficient heart sound detail information,while effectively removing noise.

关 键 词：心音信号 小波收缩 阈值函数 启发式阈值规则 

分 类 号：R540.4[医药卫生—心血管疾病] TN911.7[医药卫生—内科学]