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Method and device for classifying and processing electrocardiogram

A processing method and electrocardiogram technology, which is applied in the field of medical electronics, can solve problems such as inaccurate electrocardiogram classification, and achieve the effect of improving the final classification accuracy and improving the reaction speed

Active Publication Date: 2015-10-28
SUZHOU INST OF NANO TECH & NANO BIONICS CHINESE ACEDEMY OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an electrocardiogram classification processing method and device for the defect of inaccurate electrocardiogram classification in the prior art, which can output more accurate electrocardiogram classification results

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  • Method and device for classifying and processing electrocardiogram
  • Method and device for classifying and processing electrocardiogram
  • Method and device for classifying and processing electrocardiogram

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] figure 1 It is a flow chart of the electrocardiogram classification processing method in Embodiment 1 of the present invention, including:

[0047] Step 101, obtaining the position of the R wave in the electrocardiogram;

[0048] Step 102, according to the position of the R wave, determine the direct eigenvalue reflecting the characteristics of the electrocardiogram;

[0049] This step can be to determine a set number of RR intervals as direct feature values, specifically:

[0050] In this step, according to the position of the R wave, the two RR intervals on the left side of the R wave, the two RR intervals on the right side, and the average RR intervals of the 12 surrounding R waves, a total of 5 RR intervals can be used as Direct eigenvalues.

[0051] It should be noted that the present invention only uses the RR interval as an example of the direct eigenvalue but is not limited thereto. It can also be other direct eigenvalues ​​that can accurately reflect the cha...

Embodiment 2

[0060] figure 2 It is a flow chart of the electrocardiogram classification processing method in Embodiment 2 of the present invention.

[0061] like figure 2 shown, including steps:

[0062] Step 201, use the R wave extraction module to extract the R wave, so as to accurately obtain the position of the R wave from the electrocardiogram.

[0063] Step 202, using the feature extraction module to extract direct feature values ​​from the electrocardiogram.

[0064] In this step, direct eigenvalues ​​are extracted according to the extracted R-sweep position. In this embodiment, the RR interval (the interval between two R waves) is taken as an example for direct eigenvalues, that is, the two RR intervals on the left side of the R wave, the two RR intervals on the right side, and the surrounding 12 The average RR interval of R waves. The 5 RR intervals are transferred to the multi-layer perceptron as direct eigenvalues.

[0065] Compared with the prior art, this implementatio...

Embodiment 3

[0087] Example 3 is an example of positive and abnormal classification on ECG data of MIT-BIH (a database for studying arrhythmia) and CCDD (China Cardiovascular Disease Database):

[0088] image 3 It is a flow chart of the electrocardiogram classification processing method in Embodiment 3 of the present invention, including:

[0089] Step 301, the R-wave extraction module uses the R-wave detection method to extract the position of the R-wave in the electrocardiogram.

[0090] The ECG R-wave detection method is as follows: firstly, the input ECG signal is filtered with a band-pass filter and the phase compensation is performed, and then the difference is processed, and then the difference signal is sorted by linear change, and then the formula d(n) is used *d(n)*log(d(n)*d(n)) performs Shannon energy conversion, and uses the average filter to filter and perform phase compensation, and then detects the maximum and minimum points, excludes false R points, and corrects Get the...

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Abstract

The invention discloses an electrocardiogram classified processing method. The method comprises the following steps of: obtaining the position of an R wave in an electrocardiogram; determining a direct characteristic value for representing electrocardiogram characteristics according to the position of the R wave; dividing the electrocardiogram into different data sections by taking the R position as the center; carrying out convolution sum and sampling on the divided data sections to obtain an inner characteristic value; and calculating the direct characteristic value and the inner characteristic value according to a pre-set algorithm to obtain a classified result. The invention further correspondingly provides an electrocardiogram classified processing device. According to the technical scheme disclosed by the invention, a more accurate electrocardiogram classified result can be output.

Description

technical field [0001] The invention relates to the technical field of medical electronics, in particular to a method and device for classifying and processing electrocardiograms. Background technique [0002] The electrocardiogram is composed of PQRST and other waveforms generated by the heart cycle activity. It is a graph that records the electrical signals generated by the heart cycle activity and draws them in a prescribed format. The R wave is the most obvious waveform in the electrocardiogram. Electrocardiogram has been widely used in the clinical examination and early warning of cardiovascular diseases, and with the rise of remote monitoring, electrocardiogram analysis is also developing for out-of-hospital, sub-healthy population and long-term monitoring, so there is a demand for automated diagnosis. [0003] Existing electrocardiogram classification methods mainly focus on expert knowledge characterization, template matching and classification on extracted features,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 董军朱洪海胡晓娟张战成
Owner SUZHOU INST OF NANO TECH & NANO BIONICS CHINESE ACEDEMY OF SCI