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An ECG Signal Denoising Algorithm Based on New Threshold Function Wavelet Transform

An electrocardiographic signal and wavelet transform technology, which is applied in the field of computer algorithms to achieve the effect of removing a variety of interference noises, complete and smooth waveforms, and avoid pseudo-Gibbs phenomenon.

Active Publication Date: 2022-07-08
JIANGSU UNIV OF SCI & TECH
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  • Description
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Problems solved by technology

[0008] Aiming at the disadvantages of the existing ECG signal denoising algorithm, the present invention proposes a new solution, that is, an ECG signal denoising algorithm based on the new threshold function wavelet transform, and constructs a method between hard threshold and soft threshold A New Threshold Function Between Combined with Wavelet Transform Algorithm for ECG Signal Denoising

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  • An ECG Signal Denoising Algorithm Based on New Threshold Function Wavelet Transform
  • An ECG Signal Denoising Algorithm Based on New Threshold Function Wavelet Transform
  • An ECG Signal Denoising Algorithm Based on New Threshold Function Wavelet Transform

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Embodiment

[0029] Embodiment: a kind of ECG signal denoising algorithm based on new threshold function wavelet transform, the algorithm steps are as follows:

[0030] Step 1: Read the original ECG signal in the MIT-BIH arrhythmia database, add analog noise, and form a noisy ECG signal.

[0031] Step 2: Determine the scale of the wavelet decomposition. 8-scale decomposition was performed when baseline drift was removed; 3-scale decomposition was performed when EMG interference and power frequency interference were removed.

[0032] Step 3: Choose different wavelet functions for different noises. Using the sym4 wavelet function as the wavelet base to remove the baseline drift; using the coif4 wavelet function as the wavelet base to remove the EMG interference and power frequency interference.

[0033] Step 4; Choose an appropriate threshold. The threshold is selected using the modified index threshold method.

[0034] Step 5: Construct a new threshold function to retain useful signals ...

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Abstract

The invention belongs to the technical field of computer algorithms, in particular to an electrocardiographic signal denoising algorithm based on wavelet transform of a new threshold function, which is suitable for removing three common electrocardiographic signal noises and adding analog noise to the original electrocardiographic signal. The signal forms the actual ECG signal polluted by noise. After that, the wavelet base is selected to decompose the noisy signal, and the baseline drift, power frequency interference and EMG interference contained in the ECG signal are decomposed into different parts through multi-layer wavelet decomposition. The wavelet coefficients generated by baseline drift are processed by smooth filtering method, and the wavelet coefficients generated by power frequency interference and EMG interference are processed by a new threshold function, and finally the ECG signal without noise is reconstructed. It has been verified that the present invention can effectively overcome the shortcomings of soft and hard thresholds, and obtain a complete and smooth denoising waveform.

Description

technical field [0001] The invention belongs to the technical field of computer algorithms, and specifically relates to an electrocardiographic signal denoising algorithm based on a new threshold function wavelet transform, which is suitable for removing three common electrocardiographic signal noises. [0002] technical background [0003] Biological signals reflect the life information of the human body. In clinical medicine, doctors usually judge the physical condition of patients by observing biological signals. Common clinical biological signals are: ECG, EEG, EMG, gastric electricity, retinal electricity and so on. Among them, the ECG signal, which is easier to detect and has more regularity, is one of the most commonly used clinical examinations and is widely used, and the electrocardiogram (ECG) is a technique for recording the patterns of ECG signals. Through the electrocardiogram, we can record the electrical activity of the normal human heart, help diagnose arrhyt...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/318G06F17/14G06F17/15
CPCA61B5/7203A61B5/7225A61B5/726
Inventor 魏雪云季正超王明郭瑞敏顾凯马澄刘莹郑威马国军李效龙朱琎黄炜嘉
Owner JIANGSU UNIV OF SCI & TECH
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