Training method for noise reduction autoencoder, noise reduction method for ECG signal, and related devices and equipment

Abstract

A denoising autoencoder training method, an electrocardiography signal denoising method, and related apparatuses and devices, which use artificial intelligence to perform electrocardiography signal denoising, and may be applied to fields such as smart electrocardiogram detection. A reference electrocardiography signal to be denoised comprising significant features such as R peak positions and R-R distances of an electrocardiography signal to be denoised is extracted from said electrocardiography signal, and denoising is performed on a remaining electrocardiography signal to be denoised by means of a target denoising autoencoder after said reference electrocardiography signal has been removed from said electrocardiography signal, to prevent the target denoising autoencoder from performing denoising processing on the significant features in said electrocardiography signal, so that said reference electrocardiography signal and the denoised remaining electrocardiography signal are superimposed to obtain a denoised electrocardiography signal, wherein the R peak positions in said electrocardiography signal are better maintained, and distortion of the denoised electrocardiography signal is reduced.

Description

technical field

[0001] The present invention relates to the technical field of artificial intelligence, in particular to a training method for a noise-reduction autoencoder, a method for reducing the noise of an electrocardiographic signal, and related devices and equipment. Background technique

[0002] With the development of artificial intelligence technology, it is gradually becoming possible to help doctors with electrocardiogram diagnosis through artificial intelligence technology. The quality of the ECG signal directly affects the accuracy of ECG signal diagnosis. The acquisition of ECG signals is usually obtained through electrodes attached to the surface of the skin. Since the electrocardiographic signal on the skin is relatively weak and easily interfered by noise, the collected electrocardiographic signal has a lot of noise, which reduces the accuracy and reliability of electrocardiographic diagnosis. In particular, the ECG collected by the wearable ECG device w...

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