Unlock instant, AI-driven research and patent intelligence for your innovation.

Automatic arrhythmia analysis method based on sampling channel fusion deep neural network

A deep neural network and arrhythmia technology, applied in the field of medical signal processing, can solve the problem that the arrhythmia analysis system is not enough to meet the accuracy requirements

Active Publication Date: 2019-10-18
烽想(山东)医疗科技有限公司
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing arrhythmia analysis system is not enough to meet the accuracy requirements of clinical applications, and to provide an automatic arrhythmia analysis method based on sampling channel fusion deep neural network

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 arrhythmia analysis method based on sampling channel fusion deep neural network
  • Automatic arrhythmia analysis method based on sampling channel fusion deep neural network
  • Automatic arrhythmia analysis method based on sampling channel fusion deep neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] Embodiment 1 Automatic arrhythmia analysis method based on deep neural network

[0026] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0027] A specific example is the MIT-BIH Arrhythmia Database (mitdb), an internationally accepted electrocardiogram database. The data and usage instructions of this database are disclosed on the well-known physiionet.org website in the industry; And it has passed manual labeling by cardiologists; from the data set, four heartbeat category combinations classified according to the AAMI standard are selected as the basis for effect evaluation, including N category (normal heartbeat or bundle branch block heartbeat), S category ( supraventricular abnormal heartbeat), V category (abnormal ventricular heartbeat), and F category (fusion heartbeat); the labels of these four categories and the corresponding relationship with the categories in the mitdb dataset are s...

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 arrhythmia analysis method based on sampling channel fusion deep neural network, which comprises: three sampling methods to generate multi-channel electrocardiogram samples; the obtained 600*1-dimensional electrocardiographic signal is amplified to 3*(600* 1) Dimensional, when the original ECG signal is two leads, it is equivalent to form a 2*3*(600*1) dimensional ECG signal sample, and the input signals obtained by different sampling methods are merged through the merging layer and input respectively The parallel lead channel is composed of serial convolutional layer units, and there is an attention layer between the merging layer and the LSTM layer unit; the convolutional layer unit includes a convolutional layer that uses one-dimensional convolution to extract one-dimensional ECG signal features and sequentially serialized One excitation unit operation and one pooling layer operation; the LSTM layer unit is connected in series with a fully connected layer whose excitation unit is softmax; output; learn the parameters of the deep neural network, and automatically identify samples; solve the shortcomings of the existing arrhythmia analysis system To meet the accuracy requirements of clinical applications.

Description

technical field [0001] The invention relates to the technical field of medical signal processing, more specifically, the invention relates to an automatic arrhythmia analysis method based on sampling channel fusion deep neural network. Background technique [0002] In recent years, auxiliary diagnostic equipment for electrocardiograms has developed rapidly. With the advancement of science and technology in the information field, especially with the development of pattern recognition technology, the function of electrocardiogram equipment is no longer just to obtain electrocardiogram signals and print electrocardiograms, but to Mining the effective data in the electrocardiogram and developing in the direction of automatic identification and statistical heart beat information. The analysis equipment with the function of automatic heartbeat recognition can provide doctors with more intuitive and effective ECG information, effectively save diagnosis time and improve the diagnosi...

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 Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/00
CPCG06N3/084G06N3/045G06F2218/08
Inventor 刘通危义民贾世祥臧睦君邹海林柳婵娟周树森
Owner 烽想(山东)医疗科技有限公司