A denoising method of electrocardiogram signal based on wavelet transform

Abstract

Provided is a denoising method of electrocardiogram signal based on wavelet transform.The method comprises the following steps: selecting a wavelet function similar to the noisy signal waveform, determining decomposition layers, and performing wavelet transform to obtain low-frequency coefficients and high-frequency coefficients; selecting a wavelet function similar to the noisy signal waveform toobtain the low-frequency coefficients and high-frequency coefficients; The high frequency coefficients of each layer are thresholded to obtain new high frequency coefficients. The first layer low frequency coefficients and the new high frequency coefficients are used for wavelet reconstruction to obtain the estimated signal. Selecting other wavelet functions similar to the signal waveform, and repeating the above steps; The signal data with better noise reduction effect are added up and averaged as clean signal data, and different size of analog noise is added to the signal data. The waveletfunction with better noise reduction effect is used respectively to obtain the corresponding signal-to-noise ratio, and the optimal wavelet function is obtained by comparison. Choosing the optimal wavelet function, changing the number of decomposition layers, adding different magnitudes of analog noise to the clean signal, calculating the signal-to-noise ratio, and comparing the optimal number ofdecomposition layers. The wavelet threshold de-noising parameters which are most suitable for noisy ECM signals are obtained.

Description

technical field [0001] The invention relates to a method for denoising a cardiomagnetic signal based on wavelet transform. Background technique [0002] Electrocardiogram technology is the most common and relatively mature technology for diagnosing heart diseases. However, with the continuous development of biomagnetic detection technology, magnetocardiography technology has become a new diagnostic method with the advantages of non-contact, high sensitivity and accuracy. Methods of Cardiovascular Disease. The magnetic signal of the heart is very weak, about 10 -10 Around T, it is only one-millionth of the strength of the geomagnetic field, and it is easily affected by the external environment. At present, the magnetic signal measured by the magnetocardiograph contains baseline drift, power frequency interference, white noise and other noises. Therefore, in order to correctly diagnose diseases, the collected magnetic signal must be noise-reduced to improve the signal-to-noi...

AI Technical Summary

Problems solved by technology

However, there are certain differences between the electrocardiographic signal and the electrocardiographic signal, which have their own characteristics and noise characteristics. The wavelet threshold denoising technology suitable for the electrocardiographic signal is not directly applicable to the electrocardiographic signal, so it is necessary to study the Wavelet Threshold Denoising Technology with Its Own Characteristics

In addition, the problem of how to determine the effect of noise reduction needs to be solved on the basis of the absence of a widely recognized clean magnetic signal as a reference signal

Images