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

Electrocardiosignal characteristic detection algorithm

An ECG signal and feature detection technology, applied in the field of medical signal processing, can solve the problem that the ECG feature detection algorithm cannot take into account the detection accuracy and real-time performance at the same time, so as to improve the R-wave detection accuracy, the detection accuracy and the detection accuracy. Effect

Inactive Publication Date: 2014-04-30
TIANJIN POLYTECHNIC UNIV
View PDF5 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem that the current ECG feature detection algorithm cannot take into account the detection accuracy and real-time performance at the same time, and propose an ECG signal feature detection algorithm with high detection accuracy and strong real-time performance

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
  • Electrocardiosignal characteristic detection algorithm
  • Electrocardiosignal characteristic detection algorithm
  • Electrocardiosignal characteristic detection algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] Specific embodiments of the present invention will be described in detail below in conjunction with technical solutions and accompanying drawings.

[0025] The present invention proposes an ECG signal preprocessing method based on lifting wavelet transform combined with an improved approximate envelope, and designs an ECG signal detection algorithm based on the slope threshold of R wave, QRS wave group starting and ending points, P wave and T wave position, figure 2 It is a specific flow chart of ECG signal preprocessing and R wave detection, and the specific implementation steps are:

[0026] 1. Preprocessing of ECG signals

[0027] According to the characteristic waveform of the ECG signal and the frequency domain distribution characteristics of the noise, using the time-frequency local characteristics of the lifting wavelet transform, the sym8 wavelet is selected as the wavelet basis function to carry out five-layer lifting decomposition of the ECG signal, extract 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

No PUM Login to View More

Abstract

The invention discloses an electrocardiosignal characteristic detection algorithm, and provides an electrocardiosignal preprocessing algorithm combining an improved lifting wavelet threshold and an improved approximate enveloping algorithm. Compared with wavelet denoising, improved lifting wavelet threshold denoising has the advantages that the signal processing time is shortened, the signal-to-noise ratio is increased, the design of an envelope function is improved, and other characteristic waves except R waves and the energy of noise are suppressed while the R-wave energy is enhanced. The characteristic detection algorithm based on a slope threshold is designed, and detection of R waves, P waves and T waves is performed respectively. The detection algorithm is simple and quick, and is suitable for parallel processing. The occupied memory space is small, and the R-wave detection rate can be up to 99.8 percent.

Description

technical field [0001] The invention belongs to the technical field of medical signal processing, in particular to the denoising of weak electrocardiographic signals interfered by severe noise and the detection of feature points. Background technique [0002] Heart disease is one of the diseases with the highest morbidity and mortality in medicine today. The prevention and diagnosis of heart disease has become one of the most important problems to be solved urgently in the medical field today. One of the main technologies used to diagnose heart disease is the electrocardiogram. For more than 100 years, the electrocardiogram, a non-invasive examination technique, has played an important role in the diagnosis of heart disease due to its advantages of simple diagnostic methods and no harm to patients. Conventional ECG monitors or ECG workstations commonly used in hospitals at present have the disadvantages of large size, high price, and inconvenient monitoring at any time. Alt...

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
IPC IPC(8): A61B5/0452
Inventor 李鸿强陈磊冯秀丽王小飞梁欢陈雪龙
Owner TIANJIN POLYTECHNIC UNIV
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