A method and device for denoising ECG signals based on optimization theory

Abstract

The invention discloses an electrocardiogram signal denoising method based on optimization theory. The electrocardiogram signal denoising method includes the steps that received electrocardiogram signals are preprocessed, and a heartbeat matrix where a heartbeat cycle is stored is acquired; optimization decomposition is conducted on the heartbeat matrix on the basis of the optimization theory, and a denoised electrocardiogram signal matrix is acquired. According to the electrocardiogram signal denoising method based on the optimization theory, by preprocessing the received electrocardiogram signals, the heartbeat matrix where the heartbeat cycle is stored is acquired, and the heartbeat matrix that contains the electrocardiogram signals and electromyogram noise can be acquired; by conducting the optimization decomposition on the heartbeat matrix, the denoised electrocardiogram signal matrix is acquired, the electrocardiogram signals and the electromyogram noise in the heartbeat matrix can be separated, accordingly, the electrocardiogram signals from which the electromyogram noise is removed can be acquired, the electromyogram noise is effectively restrained, and meanwhile the efficient information of the electrocardiogram signals is retained. In addition, the invention further discloses an electrocardiogram signal denoising device based on the optimization theory. The electrocardiogram signal denoising device based on the optimization theory has the same beneficial effects as the electrocardiogram signal denoising method.

Description

technical field [0001] The invention relates to the field of biomedical signal processing, in particular to an electrocardiographic signal denoising method and device based on optimization theory. Background technique [0002] With the development of clinical medicine, electrocardiogram (ECG, electrocardiographic signal, electrocardiographic signal) has become one of the most important tools for diagnosing heart disease. The acquisition of ECG signals is usually obtained by placing corresponding electrode sensors on the upper body of the subject to be measured. And the ECG signal inevitably introduces some noise in the measurement process, such as power frequency noise, baseline drift, EMG noise and so on. How to effectively eliminate all kinds of interference and noise and accurately extract useful ECG waveform is an important content of intelligent diagnosis of heart disease. [0003] In the prior art, the method for denoising an ECG signal is mainly a filter-based metho...

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Problems solved by technology

However, although the above method can achieve better results in denoising baseline drift and power frequency noise, the noise spectrum of electromyographic noise (EMG, electromyographic noise) will overlap with the spectrum of the denoised ECG signal, The above methods cannot effectively remove the myoelectric noise with overlapping spectra, and cannot effectively suppress the myoelectric noise

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