基于活动性检测动态估计噪声的心音降噪算法
Heart sound denoising algorithm based on the dynamic estimation of noise via activity detection
许春冬 1辛鹏丽 1闵源 1应冬文 2周静 1李海兵1
作者信息
- 1. 江西理工大学信息工程学院,江西赣州 341000
- 2. 江西理工大学信息工程学院,江西赣州 341000;中国科学院大学电子电气与通信工程学院,北京 100049
- 折叠
摘要
针对基于小波分解和最优改进对数幅度谱估计的心音降噪算法存在噪声残留和心音失真的问题,提出一种基于心音活动性检测(HSAD)动态估计噪声的心音降噪算法.通过设计的HSAD判断当前心音帧是否为基础心音帧(FHS),根据判断结果分别采用改进最小值控制递归平均(IMCRA)算法和递归平滑算法对噪声功率进行动态估计与更新,采用非因果先验信噪比,实现心音信号的降噪.实验结果表明,提出算法能更好在提升降噪性能的同时,降低FHS的失真.
Abstract
Aiming at the problems of noise residue and heart sound distortion in the wavelet decomposition based denoising algo-rithm and the optimally modified log-spectral amplitude estimator based denoising algorithm,an improved heart sound denoising algorithm based on dynamic noise estimation by the heart sound activity detection(HSAD)was proposed.The designed HSAD was used to judge whether the current heart sound frame was the fundamental heart sound(FHS)frame.According to the judg-ment results,the improved minimum control recursive average(IMCRA)algorithm and the recursive smoothing algorithm were used to dynamically estimate and update the noise power,at the same time,the noncausal prior signal-to-noise ratio was com-bined to complete the noise reduction of heart sound signal.Experimental results show that the proposed algorithm can improve the noise reduction performance and reduce the distortion of FHS.
关键词
心音降噪/小波分解/心音活动性检测/改进的最小值控制递归平均/递归平滑/噪声功率估计/非因果先验信噪比Key words
heart sound denoising/wavelet decomposition/heart sounds activity detection/improved minimum controlled recur-sive averaging/recursive smoothing/noise power estimation/noncausal prior signal-to-noise ratio引用本文复制引用
基金项目
国家自然科学基金项目(11864016)
国家自然科学基金项目(61671442)
江西省研究生创新专项基金项目(YC2020-S468)
出版年
2024
NETL
NSTL
万方数据