心电信号基线漂移噪声去除算法研究

Research on Removal of Baseline Wander in ECG Signals

Abstract

ECG signals can be used to detect and diagnose heart disease.In practice,the ECG signals are often corrupted by baseline wanders that are mainly caused by respiratory activity, body movements,skin-electrode interface,varying impedance between electrodes and skin due to poor electrode contact and perspiration.The presence of baseline wanders can degrade the ECG signal quality and may severely affect the PQRST morphologies.Thus,removal of BW has become an crucial first step in most ECG signal processing applications including cardiac arrhythmias recognition,heart rate variability analysis,continuous blood pressure measurement and so on.

ECG signal is a kind of non-stationary and non-linear signal.The traditional methods of removing the baseline wander in the ECG signal are often due to excessive or incomplete denoising when the ECG signal is denoised,which easily results in the loss of a large amount of nonlinear characteristic information.This will destroy the dynamic characteristics of the ECG signal itself,which will adversely affect the subsequent analysis of ECG information.

In view of the non-stationary and non-linear characteristics of ECG signal,this paper discusses the application of two kinds of signal decomposition algorithms in the baseline wander removal of ECG signals,namely the variational mode decomposition algorithm and the singular spectrum analysis algorithm.Variational Mode Decomposition was proposed by Konstantin Dragomiretskiy in2014.Variational mode decomposition is a new,entirely non-recursive signal decomposition method,it can decompose the given signal into a set of modes which around the center frequencies.The variational mode decomposition can be used to decompose the ECG signal into several modes.Then removing the mode corresponding to the baseline wander and reconstructing the remaining modes can obtain the ECG signal after the baseline wander is removed.The Singular Spetrum Analysis method was first proposed by Colebrook in1978.Singular spectrum analysis is a powerful method for studying nonlinear time series data.It can extract the different components of the original time series.With SSA applied,the ECG signal can be decomposed into trends,oscillations or noise components based on the singular value decomposition.Only the first eigenvalue component that may be interpretable as basic trend is selected to reconstruct the BW signal and then removal it from the ECG signal.

In this paper,we use MATLAB as a simulation tool,use the ECG signals as simulation signals which are provided by arrhythmia database of Massachusetts Institute of Technology.

辽宁师范大学硕士学位论文

We used the advantages of variational mode decomposition and singular spectrum analysis in processing non-stationary signals,and studied how to remove the baseline wander in ECG signals.The experimental results show that compared with the existing baseline wander removal algorithm,the two denoising algorithms proposed in this paper not only are more adaptive but also perform better in terms of correlation coefficient and signal-to-noise ratio. Key Words：ECG Signal；BW Removal；VMD Algorithm；SSA Algorithm

心电信号基线漂移噪声去除算法研究

摘要.....................................................................................................................................I Abstract......................................................................................................................................II 1绪论.. (1)

1.1研究背景与意义 (1)

1.2国内外研究现状 (2)

1.3论文的主要研究内容 (4)

1.4本文章节安排 (4)

2心电信号及基线噪声去除概述 (6)

2.1心电信号概述 (6)

2.2心电信号中常见噪声 (7)

2.3心电数据库概述 (9)

2.4基线噪声去除算法概述 (10)

2.5基于EMD去除心电信号基线漂移算法 (11)

2.5.1经验模态分解算法 (11)

2.5.2基于EMD去除基线漂移 (13)

2.5.3EMD分解实验与分析 (14)

2.5.4经验模态分解存在的主要问题 (16)

2.6小结 (17)

3基于变分模态分解去除心电信号基线漂移算法研究 (18)

3.1变分模态分解算法 (18)

3.2基于VMD去除心电信号中的基线漂移 (19)

3.2.1分解参数选择 (20)

3.2.2基线漂移去除 (22)

3.2.3有效性验证 (22)

3.3基于VMD和EMD去心电基线结果对比 (23)

3.4小结 (24)

4基于奇异谱分析去除心电信号基线漂移算法研究 (25)

4.1奇异谱分析算法 (25)

4.2MEMD和HVD算法介绍 (27)

4.2.1MEMD算法 (27)

4.2.2HVD算法 (28)

4.3仿真结果及讨论 (29)

4.3.1基于SSA去除心电基线算法仿真 (30)

4.3.2基于HVD和MEMD去除心电基线算法仿真 (31)

4.3.3对比与讨论 (33)

4.4小结 (33)

5总结与展望 (34)

5.1总结 (34)

5.2进一步的研究与展望 (34)

参考文献 (35)

攻读硕士学位期间发表学术论文情况 (38)

致谢 (39)

1绪论

1.1研究背景与意义

现代社会中，科学技术的发展日新月异，我们的生活也和科技紧密相连，近些年最为人称道的要数移动支付的流行，极大地提高了我们生活的方便快捷程度。2009年，IBM 提出了“智慧地球”理念[1]，我国也从那时开始加大了对“智慧医疗”的研究力度，希望可以改善我国目前存在的就诊难、看病贵、救治效率低的现状。

智慧医疗结合了网络信息技术与生命科学等专业，近年来从整体上提高了我国的医疗水平[2]。智慧医疗的应用需要通过体域网[3]收集和处理来自人体的信息来实现，体域网的应用实现了智能检测和远程监控等功能[4]，患者随身佩戴体域网中的无线传感器既可以随时监测生命体征信号，又不会影响日常工作和生活，还能在一定程度上缓解目前的医疗资源紧张现状，提高医疗效率，达到及时救治和降低死亡率的目的。体域网系统在使用过程中，存在着一些难点，如对生命体征信号的分析处理等，信号分析处理的效果又与信息的可靠性有着紧密的关系。

生命体征信号有很多种，其中，心电信号（Electrocardiogram，ECG）是众多生命信号中的重中之重[5]。心脏对人体的重要性是不言而喻的，它的主要功能是为血液提供压力，将血液运输到身体每个部位，以不停地跳动来确保一切生命体征的正常[6]。社会和时代的进步是一把双刃剑，我们不能只乐观于经济的腾飞，却对给人们带来的生活压力和健康问题不予理睬，其中与心脏相关的疾病日渐增加，成为了人们不可忽视的问题。

据《中国心血管疾病报告2017》[7]统计，到2017年，我国心血管疾病患病人数已经高达2.9亿，心血管疾病已经成为威胁我国居民身体健康的首要原因，随之而来的经济负担也在逐年增加。据统计，全球每年大约有1750万人死于心血管方面的疾病，而我国在其中所占的比例就在18%左右[8]，真实的数据下，凸显了我国居民的健康状况堪忧、医疗水平还具有很大的提高空间，仅从死亡率比例来看，关于心脏方面的疾病，必须得到重视。

通过调查报告可以看出，心血管疾病已经对人类健康构成严重威胁，通过对心电信号的检测，能够评价心脏功能的健康程度。而在对心电信号自动分析时[9]，只有还原信号的真实性，才能更好地对后续过程进行分析，了解心脏情况的工作情况，所以首要任务是处理心电信号的噪声，将噪声降到最低，因为在信号的采集、放大、检测和记录过程中，来自外界的各种噪声可能导致信号中基线漂移（Baseline wander，BW）的产生，这对后续的信号分析会造成很大的干扰，所以去除基线漂移是至关重要的一个步骤。