Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Intelligent analysis method for electrocardiogram containing noise tag and electrocardiograph

An intelligent analysis and electrocardiogram technology, applied in the field of medical devices, can solve problems such as performance degradation, and achieve the effect of small calculation and accurate prediction results

Active Publication Date: 2022-03-18
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF8 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Convolutional neural networks can easily overfit to mislabeled training data, leading to significant performance degradation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Intelligent analysis method for electrocardiogram containing noise tag and electrocardiograph
  • Intelligent analysis method for electrocardiogram containing noise tag and electrocardiograph
  • Intelligent analysis method for electrocardiogram containing noise tag and electrocardiograph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The present invention will be further described below in conjunction with accompanying drawing.

[0025] like figure 1 As shown, the present invention provides a deep learning-based intelligent analysis method for electrocardiograms containing noise labels, which can reduce the negative impact of noise labels, including the following steps:

[0026] S1. First build a simple 11-layer lightweight convolutional neural network as the basis of the classification task, and input the ECG dataset containing noise labels, and perform basic data learning and training, and save after four batches of training Model.

[0027] S2. Use the fourth batch of models to predict the labels of all the data in the training set, and then perform data cleaning on the training set data (that is, predict, compare, and delete data with different results), and remove the data inconsistent with the predicted results from the data set. Delete, the remaining data form the filtered training set, use ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides an intelligent analysis method for an electrocardiogram containing a noise label and an electrocardiograph, and the method comprises the steps: firstly building a lightweight convolutional neural network as the basis of a classification task, inputting an electrocardiogram data set containing the noise label, carrying out the basic data learning training, and storing a model after the training; due to network characteristics, the convolutional neural network is very easy to over-fit with training data marked wrongly, so that the performance is obviously reduced. The invention provides a classification algorithm constructed based on data cleaning and an anti-noise label loss function, the problem that the accuracy rate of electrocardiogram diagnosis is reduced due to noise labels can be effectively relieved, and an obvious effect can be achieved at the noise degree of 10%-50%. In addition, the method is small in calculation amount and can be suitable for various electrocardiographs.

Description

technical field [0001] The invention relates to the technical field of medical devices, in particular to an intelligent analysis method for an electrocardiogram containing noise tags and an electrocardiogram instrument. Background technique [0002] The "China Cardiovascular Disease Report 2018" released by the National Center for Cardiovascular Diseases shows that the prevalence of cardiovascular disease (CVD) in my country is on the rise, and the number of CVD patients is estimated to reach 290 million. In recent years, the mortality rate of cardiovascular disease still ranks first, higher than other diseases. Arrhythmia is a common disease of the cardiovascular system, frequently-occurring disease, seriously endangering the health of the human body. Electrocardiogram is the most convenient, effective, cheap and widely used traditional method for diagnosing cardiac arrhythmia. [0003] ECG signals can intuitively reflect the changes in the heartbeat rhythm and the activi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/318A61B5/00G06N3/04G06N3/08
CPCA61B5/318A61B5/7203A61B5/7264A61B5/7267G06N3/08G06N3/045
Inventor 刘昕雯王欢李宗瑾
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com