Electrocardiosignal denoising method based on morphology and EMD (empirical mode decomposition) wavelet threshold value

A technology based on morphology and ECG signals, applied in the field of biomedical signal noise processing, can solve the problems of lack of adaptability of wavelets, and achieve the effects of good adaptability, easy implementation and simple method.

Inactive Publication Date: 2014-12-03
CHONGQING UNIV OF POSTS & TELECOMM
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However, the basis function of the wavelet is fixed, and the multi-

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  • Electrocardiosignal denoising method based on morphology and EMD (empirical mode decomposition) wavelet threshold value
  • Electrocardiosignal denoising method based on morphology and EMD (empirical mode decomposition) wavelet threshold value
  • Electrocardiosignal denoising method based on morphology and EMD (empirical mode decomposition) wavelet threshold value

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[0036] The specific implementation manner and working principle of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0037] See attached figure 1 , a method for denoising ECG signals based on morphology and EMD-like wavelet thresholds, performed according to the following steps:

[0038] First enter step 1: the present embodiment selects No. 203 electrocardiographic data whose time length is 10s in the MIT-BIT arrhythmia database as the electrocardiographic signal f to be processed, and its waveform is as follows figure 2 As shown, the acquired ECG signal f is processed by the morphological filtering method, and the baseline drift f in the ECG signal f is removed 1 get signal f 2 ,Specific steps are as follows:

[0039] Step 1-1: Perform one open-close operation and one close-open operation on the ECG signal f at the same time, that is, perform (fοk)k and (fk)οk operations on the signal at the same time, and th...

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Abstract

The invention discloses an electrocardiosignal denoising method based on morphology and EMD (empirical mode decomposition) wavelet threshold value. The electrocardiosignal denoising method comprises the following steps: firstly, the mathematical morphology filter method is adopted to perform primary filtering on an electrocardiosignal to filter baseline drift in the electrocardiosignal, then, the EMD method is adopted to decompose the obtained electrocardiosignal and obtain a noise dominant component and a useful signal dominant component through classification, the threshold value denoising method is adopted to perform secondary filtering on the electrocardiosignal, and finally, the EMD method is adopted to reconstruct the electrocardiosignal to obtain the noise-filtered electrocardiosignal. The invention has the following remarkable effects: the method is simple and easy to implement; the morphological filter method, the EMD method and the threshold de-noising method are combined in an organic manner; compared with the traditional denoising method, the electrocardiosignal denoising method can comprehensively and effectively remove electrocardiosignal noise, keeps the useful information in the electrocardiosignal, and provides more valuable reference for change of cardiac functions and diagnosis of cardiac diseases.

Description

technical field [0001] The invention relates to the technical field of biomedical signal noise processing, in particular to an electrocardiographic signal denoising method based on morphology and EMD wavelet threshold. Background technique [0002] ECG signal is one of the vital signs of human beings, which can accurately reflect the information of the heart from different levels, and provides a very valuable reference for the change of heart function and the diagnosis of heart disease. [0003] The ECG signal is a non-stationary weak signal with strong randomness and real-time changes. Its frequency is mainly concentrated in 0.05 ~ 100HZ, its energy is mainly concentrated in 0.5 ~ 45HZ, and its amplitude is between 0.05 ~ 5mv. There are three main types of noise in the ECG signal: power frequency interference caused by the 50HZ power supply and high-order harmonics from the equipment, baseline drift caused by body movement, breathing and acquisition engineering, and muscle...

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IPC IPC(8): G06F19/00A61B5/0402
Inventor 庞宇张磊磊林金朝吴健李章勇王伟罗志勇周前能李国权
Owner CHONGQING UNIV OF POSTS & TELECOMM
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