An EMG Noise Filtering Method for ECG Signals

Abstract

The invention relates to an electromyographic noise filtering method for electrocardiographic signals. First, the wavelet-Wiener filter is used to gently filter the overall signal, which fully retains the details of the high-frequency components while filtering out the electromyographic noise of the high-frequency components of the ECG, and then the moving average filter is used to further filter out the remaining noise; After the overall wavelet-Wiener filtering is performed, the low-frequency components are additionally processed. The Q point and the S point are first located, and the low-frequency components between the two heart beats are cut out. Only the low-frequency components are subjected to moving average filtering, so as to further filter out the heart. The residual EMG noise of the electrical low-frequency components; before the two-step filtering, the severity of the EMG noise in the signal is evaluated, so as to set the parameters of the filter adaptively; Points at half the order of the moving average filter. The invention can reduce the noise in the electrocardiogram signal with the minimum distortion, and can be used as an effective tool for denoising the electrocardiogram signal.

Description

technical field [0001] The invention relates to an electromyographic noise filtering method for electrocardiographic signals. Background technique [0002] The ECG signal records the electrical activity of the heart, and the shape of each component conveys many important clinical information, which objectively reflects the health of the heart to a certain extent. However, due to the ECG acquisition environment and its own characteristics, it is inevitably interfered by many factors during the acquisition process. A common type of interference is EMG noise. Myoelectric noise is usually caused by muscle contraction or relaxation during human activities. The main energy is concentrated between 20 and 120 Hz, and it appears as an irregular and rapidly changing sawtooth waveform in the electrocardiogram. EMG noise will lead to poor ECG signal quality, and severe EMG interference may even overwhelm the ECG signal. In order to improve the quality of the ECG signal and prevent th...

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Problems solved by technology

However, both methods have defects: first, both methods use a fixed time window to preserve the QRS complex, which will cause some low-frequency components to be preserved, resulting in the inability to remove this part of the myoelectric noise; second, this The two methods do not deal with the connection between the high-frequency component and the low-frequency component, which leads to distortion of the connection between the high-frequency component and the low-frequency component of the signal

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