An ECG Signal Noise Reduction Method Based on Improved Residual Dense Network
An ECG signal and dense network technology, applied in medical science, diagnosis, diagnostic recording/measurement, etc., can solve the problems of uncertain noise types, gradient disappearance, and loss of useful information, etc., to improve accuracy and work efficiency, improve Generalization ability, the effect of removing baseline drift
Active Publication Date: 2022-06-03
SHANDONG ARTIFICIAL INTELLIGENCE INST
View PDF13 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
However, ECG signals often contain a variety of noises, and the noise types cannot be determined, and the effect of a single denoising method is not ideal
In the traditional noise reduction method, due to the aliasing of the noise signal and part of the ECG signal waveform, it is easy to cause signal waveform distortion and lose a lot of useful information
Some deep learning denoising methods, such as autoencoders, generative confrontation network methods, etc., have problems such as gradient disappearance or gradient explosion, so it is difficult to train deeper networks, which affects subsequent research on ECG 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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment 1
Embodiment 2
[0050] In step c), the clean ECG signal and the noisy ECG signal will be divided by 80% and 20% respectively
Embodiment 3
[0058] d-6) the global residual H
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
Login to View More
Abstract
An ECG signal denoising method based on an improved residual dense network. The residual dense network has the ability to reuse features, which reduces the computational cost while achieving ECG signal denoising. In the process of applying the residual dense network, there is no need to artificially set parameters based on experience, avoiding empirical errors, and improving the generalization ability of the model. In the improved residual dense network, the input of each improved residual block is fused with the output of all the previous improved residual blocks; by removing the noise of the ECG signal through this network, the output of all the previous improved residual blocks can be obtained. Output, enhanced feature propagation; as the network deepens, there will be no problems such as gradient messages and gradient explosions. Considering the local and global features of the signal at the same time, it can not only capture the local features of the signal and preserve useful medical features, but also capture the global features of the signal and stabilize the training process.
Description
A Denoising Method of ECG Signal Based on Improved Residual Dense Network technical field The present invention relates to the technical field of ECG signal noise reduction, be specifically related to a kind of heart based on improved residual dense network Electrical signal noise reduction method. Background technique [0002] The electrocardiogram is the main basis for the diagnosis of cardiovascular disease, and is an important auxiliary means for cardiovascular doctors to check. ECG signals contain important medical information such as physiology and pathology, and reflect the physiological health of various parts of the heart to a certain extent. important biomedical signals. However, due to the weak and random characteristics of ECG signals, and often in clinical applications Accompanied by a large amount of noise, it is easy to cause ECG waveform distortion, which will affect the identification of each band of the signal, and even affect the medical treatment. ...
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
Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/318A61B5/346
CPCA61B5/318A61B5/346A61B5/7203A61B5/7207A61B5/7225A61B5/7264
Inventor 陈长芳相潇学舒明雷刘瑞霞高天雷单珂卞立攀
Owner SHANDONG ARTIFICIAL INTELLIGENCE INST
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 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