Automatic heart sound diagnosis system based on deep learning

An automatic diagnosis and deep learning technology, applied in the field of medical signal processing, can solve problems such as the inability to classify heart sound signals, achieve the effect of simple, fast, high-precision preprocessing, and improve classification accuracy

Active Publication Date: 2021-12-31
HUAZHONG UNIV OF SCI & TECH +1
View PDF8 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the above defects or improvement needs of the prior art, the present invention provides a heart sound automatic diagnosis system based on deep learning to solve the technical problem that the prior art cannot accurately classify heart sound signals

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
  • Automatic heart sound diagnosis system based on deep learning
  • Automatic heart sound diagnosis system based on deep learning
  • Automatic heart sound diagnosis system based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0037] In order to achieve the above object, the present invention provides a heart sound automatic diagnosis system based on deep learning, including:

[0038] The heart sound signal processing module is used to preprocess the heart sound signal, and divide the preprocessed heart sound signal into a plurality of heart sound signal segments of equal length;

[0039] Specifically, the method for...

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 discloses an automatic heart sound diagnosis system based on deep learning, and belongs to the field of medical signal processing, and the system comprises: a heart sound signal processing module which is used for preprocessing a heart sound signal and segmenting the preprocessed heart sound signal into a plurality of heart sound signal segments with the same length; and a heart sound detection module which is used for respectively inputting the obtained heart sound signal fragments into a pre-trained heart sound detection model to obtain a heart sound category of each heart sound signal fragment, and synthesizing the heart sound type of each heart sound signal segment to obtain the heart sound type of the to-be-detected heart sound signal. According to the automatic heart sound diagnosis system based on deep learning provided by the invention, the heart sound signals are automatically detected in an end-to-end manner, the multi-level time sequence features extracted by the LSTM and the local features extracted by the CNN are combined, the advantages of the CNN local feature extraction capability and the LSTM long-term dependence capture capability are fully utilized, and the classification precision is greatly improved.

Description

technical field [0001] The invention belongs to the field of medical signal processing, and more specifically relates to a heart sound automatic diagnosis system based on deep learning. Background technique [0002] Heart disease has become the number one killer threatening human health. About 17 million people die from heart disease every year. Early diagnosis of heart disease is crucial to reducing the mortality rate. Heart sound (PCG) is the sound produced by the mechanical movement of the heart and cardiovascular system, which contains early pathological information of cardiovascular diseases, and has been proven to be effective in detecting potential early cardiovascular diseases. At present, clinicians mainly use traditional stethoscopes to identify heart sounds, and the accuracy of diagnosis results greatly depends on the doctor's personal experience. At the same time, there is a serious shortage of doctor resources in many countries. Heart sounds are used as a preli...

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): A61B7/02G06K9/62G06N3/04G06N3/08
CPCA61B7/02G06N3/08G06N3/044G06N3/045G06F18/2415
Inventor 李强张浩波张鹏
Owner HUAZHONG UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap