ECG signal denoising method based on fusion of improved emd and threshold method

Abstract

The invention proposes an electrocardiographic signal denoising method based on the fusion of improved EMD and a threshold method, which belongs to the technical field of signal filtering. The present invention solves the modal aliasing problem by superimposing white noise with different weight coefficients, solves the endpoint problem by the method of the least squares support vector machine, constructs the upper and lower envelopes of the signal by the method of conformal spline interpolation, and utilizes the conformal segmentation method to construct a cubic spline interpolation with second-order approximation accuracy, fewer segments, and a small amount of calculation. This method can suppress the problem of overshoot / undershoot in envelope fitting. Through the orthogonality and energy properties of the decomposed IMF , put forward the criterion of IMF component "screening" termination, which ensures the orthogonality and completeness of EMD decomposition, judges the amount of noise in the screened IMF signal through the principle of mutual information, and decides whether to filter it , which increases the rapidity of the EMD algorithm; improves the threshold function, which combines the advantages of soft and hard thresholds to filter the IMF containing noise.

Description

technical field [0001] The invention relates to a method for denoising electrocardiographic signals, in particular to a method for denoising electrocardiographic signals based on the fusion of improved EMD and a threshold method, and belongs to the technical field of signal filtering. Background technique [0002] ECG signal is a typical non-stationary and weak bioelectrical signal, which is widely used in the diagnosis and treatment of various heart diseases. ECG signals are often accompanied by very serious high-frequency and low-frequency noise, and the noise frequency band often overlaps with the ECG signal frequency band, making filtering preprocessing difficult. [0003] Traditional biomedical signal processing is mainly based on Fourier theory. Fourier signal processing technology is almost irreplaceable in signal spectrum analysis and associated signal processing fields such as data compression, signal detection, and filtering. However, the integral interval of the...

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Problems solved by technology

The quality of the envelope curve fitting in the method directly affects the decomposition results. The original method of cubic spline function interpolation is completed with the extreme point as the known point. Because of the inhomogeneity of the extreme point distribution, the It is the fitting of non-uniform points, which will cause the problem of extreme undershoot or overshoot, resulting in a large error in decomposition

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