远程心电监护中ECG信号的提取

远程心电监护中采集到的心电信号往往包含较严重的噪声干扰,给医生的诊断带来了困难,针对这一问题,介绍了一种基于人工神经网络和自适应噪声抵消的ECG信号自动提取方法;用一个三层BP网络来代替自适应抵消中常用的线性滤波器,对原始ECG信号进行自适应滤波。通过Matlab/Simulink进行仿真;结果表明该方法能够很好地适应噪声的非线性特性,用于远程心电监护中强噪声背景下的ECG信号提取,取得了令人满意的效果。

Detection of ECG in Remote Electrocardiographic Monitoring

There is always lots of noise in the electrocardiographic in romete ECG monitoring,which brings much trouble to diagnoses.This article introduced a method of the detection of ECG from a very noisy environment based on artificial neural network and self-adaptive noise cancellation.A three-lays BP network was built to instead of the linear filter of a self-adaptive noise cancellation and the original ECG was filtered by it.Emulated by Matlab/Simulink,the results showed that the method had good ability of nonlinear mapping,and was very effective for the detection of ECG in a very noisy environment in remote electrocardiographic monitoring.