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Arrhythmia classification method based on multilead information fusion

A technology of arrhythmia and classification methods, applied in the field of medical signal processing, can solve the problems of lack of integrity and diversity of multi-lead ECG signals, and achieve high classification performance

Active Publication Date: 2020-09-15
UNIV OF SCI & TECH OF CHINA
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Problems solved by technology

However, at present, the existing research on ECG analysis lacks a clear mechanism to fuse the integrity and diversity of multi-lead ECG signals.

Method used

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  • Arrhythmia classification method based on multilead information fusion
  • Arrhythmia classification method based on multilead information fusion
  • Arrhythmia classification method based on multilead information fusion

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Embodiment Construction

[0054] In this embodiment, a method for classifying arrhythmia based on multi-lead information fusion includes the following steps:

[0055] Step 1. Obtain the original ECG signal and its corresponding label y, and down-sample the original ECG signal to obtain the sampled ECG signal; perform clipping or zero padding on the sampled ECG signal to obtain the preprocessed ECG signal X , and the preprocessed ECG signal X contains d leads.

[0056] Step 1.1. Obtain the original ECG signal and its corresponding label required for the experiment from the public database of the China Physiological Signal Challenge (CPSC) 2018. The public database of CPSC 2018 provides 6877 12-lead ECG records with a time length ranging from 6 seconds to 60 seconds. Records were collected from 11 hospitals with a sampling rate of 500 Hz. These ECG records contained nine rhythm types, normal rhythm and eight arrhythmias, as shown in Table 1.

[0057] Table 1: Data distribution of CPSC2018 public datab...

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Abstract

The invention discloses an arrhythmia classification method based on multilead information fusion. The method comprises the steps: 1. carrying out downsampling, filling-in and pretreatment of fixed length on original multilead electrocardiogram signals; 2. constructing a classification model, which is composed of a plurality of single branch networks and is responsible for specially processing corresponding mono-lead electrocardiogram signals, and meanwhile, optimizing parameters of the classification model by using a multi-loss cooperative optimization strategy; 3. employing ten-fold cross verification training on a public data set, and evaluating the above-mentioned model; and 4. achieving an arrhythmia classification task by using the trained model. According to the method, informationlearning of the multilead electrocardiogram signals is maximized through fusing integrity and diversity of the multilead electrocardiogram signals by the multi-loss cooperative optimization strategy,and high-accuracy automatic detection on arrhythmia can be achieved, so that assistance is provided for clinical diagnosis, and early warning is provided for a patient employing wearable equipment.

Description

technical field [0001] The invention relates to the field of medical signal processing, in particular to a method for detecting arrhythmia from electrocardiogram signals. Background technique [0002] Cardiovascular disease (CVD) is the leading cause of death worldwide. According to the World Health Organization, an estimated 17.9 million people died from CVD in 2016, accounting for 31% of global deaths. Arrhythmia, the most common form of cardiovascular disease, is an irregularity in the electrical activity of the heart. Many types of arrhythmias are harmful to health and even life-threatening, such as ventricular tachycardia and ventricular fibrillation are fatal arrhythmias. Therefore, early detection and prevention of arrhythmia are particularly important. [0003] Electrocardiogram (ECG) is widely used in the diagnosis of arrhythmia due to its non-invasiveness and low cost. Using electrodes placed on the skin, an EKG records the electrical activity of the heart over...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0402A61B5/0464A61B5/0428A61B5/00A61B5/308A61B5/363
CPCA61B5/7267
Inventor 陈勋张静梁邓刘爱萍高敏张旭陈香
Owner UNIV OF SCI & TECH OF CHINA
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