基于小波和形态学的窦房结电图消噪算法研究

SNE denoising algorithm based on wavelet and morphology

窦房结电图(SNE)是反映窦房结电活动的一种高分辨率的心电图,在临床医学上主要用于研究心律失常。为了提高临床诊断效率,提出了一种基于小波分析和数学形态法的消噪算法。该算法采用线性结构元素的形态滤波器消除SNE信号中的基线漂移,使用小波软阈值消噪法去除高频噪声,从而得到信噪比高的SNE信号。实验表明该算法可有效地对SNE信号进行消噪处理。

Sinus node electrogram （SNE） is a reflection of the sinus node electrical activity as a high-resolution ECG, mainly used in the clinical study arrhythmias. In order to improve the efficiency of clinical diagnosis,this paper presents a denoising algorithm based on wavelet and morphology. This algorithm removes baseline drift by morphology filter which with a linear structure elements. And then it uses wavelet soft threshold denoising method to remove high frequency noise, resulting in a high signal to noise ratio SNE signal. Experiments show that the algorithm can effectively SNE signal denoising.