Electrocardiogram electrocardiosignal classification method with multi-scale characteristics combined

A multi-scale feature, ECG signal technology, applied in the multi-scale feature fusion, the classification of normal and various abnormal ECG signals, can solve the signal feature redundancy, resolution is not enough, can not be well expressed Signal and other problems to achieve the effect of improving classification accuracy and reducing classification time

Active Publication Date: 2015-02-25
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, the wavelet transform can only provide sufficient frequency resolution for low frequencies, but not enough for high frequencies, so that the features extracted in the wave

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  • Electrocardiogram electrocardiosignal classification method with multi-scale characteristics combined
  • Electrocardiogram electrocardiosignal classification method with multi-scale characteristics combined
  • Electrocardiogram electrocardiosignal classification method with multi-scale characteristics combined

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[0018] The following describes in detail the fast multi-scale feature fusion technology method provided by the present invention to improve the classification accuracy of heartbeat signals in conjunction with the accompanying drawings.

[0019] figure 1 The flow chart of the heartbeat signal classification method includes the following steps:

[0020] Step S101: Read all the ECG signals in the database.

[0021] Step S102, removing the baseline and high frequency noise of the signal.

[0022] (1) Apply 200ms and 600ms bandwidth median filters to remove ORS complexes and P&T waves, and subtract them from the original signal to obtain a baseline-removed signal.

[0023] (2) Apply a low-pass filter to remove high-frequency noise in the signal.

[0024] Step S103, ECG signal segmentation: first find the reference point (ie R point) of the ECG signal, and use the reference point forward 99 sampling points and backward 100 sampling points as the segmented heartbeat signal for one cycle.

[0025...

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Abstract

The invention provides an electrocardiogram electrocardiosignal classification method with multi-scale characteristics combined. The method comprises the steps that (1), all electrocardiosignals in a database are read, and a base line and high-frequency noise in the electrocardiosignals are removed; (2), the electrocardiosignals are divided; (3), wavelet packet decomposition of the electrocardiosignals is calculated, and a fourth layer of wavelet packet decomposition coefficient is obtained; (4), electrocardiosignal characteristics extracted in a plurality of periods are arranged to form M-dimensional data, a generalized multidimensional independent component analysis method is applied to the M-dimensional data, and demixing matrixes of all modes are obtained; (5), a heartbeat signal to be tested is input, the fourth layer of wavelet packet decomposition coefficient is obtained through the step 1, the step 2 and the step 3, M-1-dimensional data are formed in an arranged mode, and the fuse characteristics of the tested heartbeat signal are obtained through the step 4; (6) the heartbeat signal fuse characteristics are classified through a classifier, and then the classification result of multiple normal and abnormal electrocardiosignals is obtained.

Description

technical field [0001] The invention is an electrocardiogram signal classification system, relates to a fast, multi-scale feature fusion technology and method, and can be used for classification of normal and various abnormal electrocardiogram signals. Background technique [0002] Cardiovascular disease is one of the diseases that cause the highest mortality in humans worldwide. The prevalence of cardiovascular disease continues to increase due to individual behavioral factors (smoking, lack of exercise, unhealthy diet), metabolic factors (hypertension, hyperglycemia, hyperlipidemia), and other factors (genetics, advanced age). Arrhythmia, as a common cardiovascular disease, is a disease of the electrical conduction system of the heart, causing medical emergencies and seriously endangering human life. [0003] An electrocardiogram, or electrocardiogram (ECG), is a standard diagnostic tool for non-invasive monitoring of the electrical activity of the heart. To detect occas...

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Application Information

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IPC IPC(8): A61B5/0452
CPCA61B5/35
Inventor 艾丹妮杨健王涌天刘越王泽宇
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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