结合小波变换和能量熵在膈肌肌电中去除心电干扰的应用

An Application of the Approach Combining Wavelet Transform and Energy Entropy to Remove Electrocardiography Interference in Diaphragmatic Electromyographic

膈肌肌电(EMGdi)信号是一种由膈肌产生并蕴含着人体呼吸系统重要生理信息的生物电信号,该信号易受自身心电(ECG)信号的严重干扰。本文在小波变换的基础上,结合信息熵理论,提出了一种新的小波能量熵阈值去心电算法。该方法在对信号各层小波系数的分析基础上,将每层的系数信息量看成一个单独的信号源,将其分成N等份的小区间,通过系数能量熵的分布特性将其分成高能量熵和低能量熵两类分别进行绝对均值阈值处理,对阈值后的小波系数进行小波重构便得到降噪后的EMGdi信号。通过实验对比结果表明,该方法有效地去除了EMG-di信号的ECG干扰信号,更大程度地保留了EMGdi的信号特征。

Diaphragmatic electromyographic （EMGdi） signal is a weak biological signal, which contains some signifi- cant physiologlcal information of our body respiration system and is susceptible to strong electrocardiography （ECG） signal interference. Based on wavelet transform and theory of information entropy, a new wavelet energy entropy threshold algorithm to remove ECG interference is proposed in this paper. On the base of analysis of wavelet coeffi- cients of each scale, the method sees the information of each scale as a single signal source, equalizes it byzones, and then divides the energy entropy into two categories （i. e. , high energy entropy and low energy entropy） through the distribution characteristics of energy entropy of each zone to conduct absolute mean value threshold. In addition, the denoised signal is reconstructed by wavelet coefficients processed. The experimental results showed that the method removed the ECG signal in EMGdi effectively and reserved the available characteristics of EMGdi better.