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Method and device for multi-scale characteristic extraction based on ECG

A multi-scale feature and extraction method technology, applied in the field of medical information processing, can solve the problem that the ECG signal cannot extract variation features, etc., and achieve the effect of strong disease discrimination ability

Active Publication Date: 2019-11-26
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] The embodiment of the present invention provides an ECG-based multi-scale feature extraction method and device, to at least solve the existing technical problem that deeper variation features cannot be extracted when performing feature extraction on ECG signals

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  • Method and device for multi-scale characteristic extraction based on ECG
  • Method and device for multi-scale characteristic extraction based on ECG
  • Method and device for multi-scale characteristic extraction based on ECG

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Embodiment 1

[0040] According to an embodiment of the present invention, an ECG-based multi-scale feature extraction method is provided, see figure 1 , including the following steps:

[0041] S101: Obtain several ECG signal identification units based on the ECG signal interception of one lead, where the ECG signal identification unit is a wave band including at least one cardiac cycle in the ECG signal of one lead;

[0042] S102: Decomposing several ECG signal recognition units into multi-scale, constructing an ECG multi-scale space;

[0043] S103: Extract multi-scale features from the ECG multi-scale space signals in the ECG multi-scale space through a preset convolutional neural network.

[0044]In the ECG-based multi-scale feature extraction method in the embodiment of the present invention, several ECG signal identification units are obtained based on the interception of the ECG signal of one lead, and the ECG signal identification unit is a wave band including at least one cardiac cy...

Embodiment 2

[0112] According to another embodiment of the present invention, a multi-scale feature extraction device based on ECG is provided, see Figure 6 ,include:

[0113] The identification unit intercepting unit 201 is configured to obtain several ECG signal identification units based on the interception of the ECG signal of one lead, and the ECG signal identification unit is a wave band including at least one cardiac cycle in the ECG signal of one lead;

[0114] The ECG multi-scale space construction unit 202 is used to decompose several ECG signal identification units into multi-scale to construct an ECG multi-scale space;

[0115] The multi-scale feature extraction unit 203 is configured to extract multi-scale features from the ECG multi-scale space signals in the ECG multi-scale space through a preset convolutional neural network.

[0116] The ECG-based multi-scale feature extraction device in the embodiment of the present invention obtains several ECG signal identification uni...

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Abstract

The present invention relates to a method and device for multi-scale characteristic extraction based on ECG. The method and device firstly obtain an ECG signal identification unit based on a lead ECGsignal interception and performs multi-scale decomposition of the ECG signal identification unit to construct an ECG multi-scale space; then ECG multi-scale space signals in the ECG multi-scale spaceare subjected to multi-scale characteristic extraction by a preset convolutional neural network; the ECG signal identification unit comprises at least one cardiac cycle band which is more conducive for the convolutional neural network to conduct ECG variation characteristic and spatial characteristic learning of myocardial infarction, and extracts variation characteristics from a deeper level fromECG signals through the preset convolutional neural network, and the variation characteristics have a strong ability to discriminate diseases, obtain spatial characteristics related to locations of the diseases based on spatial learning ability of the convolutional neural network, and provide important practical reference value for doctors to predict the locations of the myocardial infarction.

Description

technical field [0001] The present invention relates to the field of medical information processing, in particular to an ECG-based multi-scale feature extraction method and device. Background technique [0002] Myocardial infarction is the most common cardiovascular disease, which is mainly caused by the corresponding downstream myocardial hypoxia caused by coronary artery blockage, which in turn leads to myocardial necrosis in this area. ECG is the main tool to measure the electrical activity of the heart. The 12-lead ECG can correspond to the corresponding heart area and is widely used in the clinical diagnosis of myocardial infarction. Clinically, determining the location of myocardial infarction is of great significance for further treatment. Experienced clinicians can determine the location of infarction according to the coupling relationship of lesions in multiple leads. For example, if the ST segment is too high and pathological Q waves occur in leads V1 and V2, it ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0452A61B5/00
CPCA61B5/7267A61B5/35A61B5/349
Inventor 李烨刘记奎苗芬闻博刘增丁
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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