线性时频分析在ECG信号分析中的应用

摘要

Objective:Electrocardio-signal (ECG) is one of the most important biological signals in the human body,which is a signal having a non-stationary and nonlinearity.In recent years,many scholars at home and abroad are committed to research in this field,because the analysis of the ECG signal is advantageous tool for the diagnosis of heart disease.This paper discusses the application of the time-frequency analysis in ECG signal using both of the short-time Fourier transform (STFT) and discrete wavelet transform(DWT).Methods:The data in this paper come from MIT-BIH database of Massa-chusetts Institute of Technology.The author apply MATLAB software for programming and discuss application of STFT and DWT in ECG signal analysis.Results:The author make Time-domain map and spectrum of STFT and signal stage DWT by programming.Conclusion:The STFT time domain graph and spectrogram of normal ECG signal and abnormal ECG signals can reflect changes in the relationship of the signal frequency and time.However,the frequency and time of the normal signal and abnormal signal are significantly different,and the energy of the normal signal with changes in time and frequency relationship in an orderly neat and less clutter around; abnormal signal energy changes with the time and frequency relationship clutter and more clutter around.The normal signal and abnormal signal are generated different discrete wavelet coefficients,followed by a discrete wavelet changes.We can easily determine the difference between the normal signal and the abnormal signal depending on the discrete wavelet coefficients.%目的:心电信号(Electrocardio-signal,ECG)是人体中最重要的生物信号之一,是一种具有非平稳性和非线性特性的信号.分析ECG信号是诊断心脏疾病的有利工具,近年来国内外很多学者致力于这方面的研究.本文探讨短时Fourier变换(STFT)和离散小波变换(DWT)这两种时频分析方法在ECG信号分析中的应用.方法:本文采用麻省理工学院的MIT-BIH数据库中提供的数据,运用MATLAB软件编程,讨论短时Fourier变换和离散小波变换在ECG信号分析中的应用.结果:通过编程,做出了正常ECG信号和失常ECG信号的短时Fourier变换的时域图和频谱图以及正常ECG信号和失常ECG信号的单级离散小波变换的结果.结论:正常ECG信号和失常ECG信号的STFT变换的时域图和频谱图都能反应出信号的频率和时间的变化关系.但是,正常信号和失常信号的频率和时间有明显不同,正常信号的能量随时间和频率的变化关系有序整齐,而且周围有较少的杂波；失常信号的能量随时间和频率的变化关系杂乱,而且周围存在较多的杂波.通过离散小波变化后,正常信号和失常信号均产生了不同的离散小波系数,根据不同的离散小波系数,可以很容易判断正常信号和失常信号的区别.