Ecg Automatic Analysis Technology Based On Wavelet Transform

With the development of the society economy and life, cardiac diseases have been one of the major diseases that harm human's health. As ECG reflects the state of the cardiac system,there is important meaning to research the Electrocardiograph (ECG) signals. Signal preprocessing and waveforms detection for ECG are the key of the ECG monitoring diagnosis system for diagnosis and therapy.Wavelet transform theory is a time-frequency method of signal analysis. It has the characteristics of multi-resolution and can be used to describe the local characteristic of signal in both time field and frequency field. Because of the extra performance in signal procesing, in the area of Biomedical Engineering,it has been widely adopted in signal detecting, feature extraction,image processing,signal compression and so on.In this paper,the principle and the characteristics of ECG are explained at first. Based on theory of wavelet transform, denoising, features waveform detection and automatic identification arrhythmia of the ECG signal are discussed.In the study of ECG signal denoising, principle of wavelet thresholding denoising method and the shortcomings of wavelet thresholding denoising method in ECG are discussed. A new denoising method based on translation invariant and Bionic translation is proposed. The experimental results indicate that the proposed methods are better than traditional wavelet thresholding de-noising methods in aspects of suppressing Pesudo-Gibbs phenomenon and saving singular points.In the study of features waveform detection, from the angle of signal processing, the theory of detecting the mutant points by wavelet transform is proposed and the relation between the characteristic points and the modulus maximum is discussed. QRS complexes, starting point and ending point of P and T wave detection algorithms are proposed. The validity of the algorithms for waveform detection and fiducial point location has all been proved using using the MIT-BIH Arrhythmia Database.In the study of automatic identification arrhythmia, the causes and the categories of arrhythmi are stated first, then introduces the main types of arrhythmia and the algorithm of identification and diagnosis arrhythmia.