Electrocardiosignal denoising method based on improved EMD (Empirical mode decomposition) and threshold method fusion

Abstract

The invention provides an electrocardiosignal denoising method based on improved EMD (Empirical Mode Decomposition) and threshold method fusion, and belongs to the technical field of signal wave filtering. The mode mixing problem is solved by adding white noise with different weight coefficients. The end point problem is solved by a method of a least squares support vector machine. Signal upper and lower envelope lines are constructed by a conformal spline interpolation method; and cubic spline interpolation with second-order approximation accuracy, few segments and small calculation quantityis constructed by a conformal segmentation method. The method can be used for inhibiting the envelope fitting overshoot / undershoot problem; IMF (Intrinsic Mode Function) component sieve termination criterion is provided by the decomposed IMF orthogonality and energy properties; the orthogonality and completeness of the EMD are ensured; the amount of noise contained in the sieved IMF signals is judged through a mutual information principle, whether the filtering processing is needed or not is determined, and the high speed of an EMD algorithm is accelerated; a threshold function is improved;the threshold function combines with the advantages of soft-hard thresholds; and the filtering processing is performed on IMF containing the 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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