Electrocardiosignal denoising method based on ESMD (extreme-point symmetric mode decomposition) method

Abstract

The invention discloses an electrocardiosignal filtering algorithm based on extreme-point symmetric mode decomposition and nonlocal means methods. An electrocardiosignal denoising method includes the steps of firstly, subjecting electrocardiosignals to extreme-point symmetric mode decomposition to obtain an IMF (intrinsic mode function) sequence; then, subjecting each IMF to nonlocal means filtering and superposing all-order IMFs and residual terms; finally, subjecting superposed signals to nonlocal means smoothing so as to obtain a final electrocardiosignal denoising result. The electrocardiosignal denoising method has the advantages that by combining the extreme-point symmetric mode decomposition method with the nonlocal means filtering method organically, the electrocardiosignal denoising method effectively improves the problem that a traditional nonlocal means algorithm is prone to signal weakening when noise pollution degree is high, so that detailed information of signal peaks and the like can be well protected while electrocardiosignal noise can be inhibited effectively.

Description

technical field [0001] The invention belongs to the field of medical signal processing, and more specifically relates to a noise reduction processing of electrocardiographic signals. Background technique [0002] The electrocardiogram is the process of electrical activity that reflects the excitement of the heart. However, as a weak signal (generally at the millivolt level), the ECG signal is easily overwhelmed by external noise. Common noises include power frequency noise, myoelectric noise, and baseline drift interference caused by patient respiration and movement. Noise has a very adverse effect on the measurement of ECG parameters, waveform recognition, and disease diagnosis. It is of great significance to study effective ECG signal noise reduction methods to improve the accuracy of heart disease diagnosis. [0003] Common ECG signal noise reduction methods include low-pass, high-pass and band-pass filtering, morphological filtering, Wiener filtering, Kalman filtering, ...

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Problems solved by technology

[0007] Aiming at the problems existing in the prior art, this application provides an ECG signal noise reduction method, which is researched and involved through ESMD, so that it is organically combined with the non-local mean filtering method. Compared with the existing method, this The method effectively improves the signal weakening problem that the traditional non-local mean algorithm tends to produce when the noise pollution is high, and can effectively suppress the noise of the ECG signal while protecting the details of the signal such as spikes.

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