A Heart Rate Variability Signal Analysis Method Based on Extreme Value Energy Decomposition Method

A signal analysis method and heart rate variability technology, applied in diagnostic recording/measurement, medical science, diagnosis, etc., can solve problems such as lack of details, inflexible segmentation, and rough frequency domain segmentation

Active Publication Date: 2020-09-01
JIANGSU HUAKANG INFORMATION TECH CO LTD
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, PSD is not a data-driven approach, and the segmentation in the frequency domain is rough, resulting in missing details and inflexible segmentation.

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
  • A Heart Rate Variability Signal Analysis Method Based on Extreme Value Energy Decomposition Method
  • A Heart Rate Variability Signal Analysis Method Based on Extreme Value Energy Decomposition Method
  • A Heart Rate Variability Signal Analysis Method Based on Extreme Value Energy Decomposition Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] The EED analysis method was used to analyze the energy distribution of the ECG of healthy people and CHF patients at different levels.

[0058] A heart rate variability signal analysis method based on extreme value energy decomposition method for healthy people, comprising the following steps:

[0059] (1) Obtain the ECG signals of healthy people from the RR interval database nsr2db of physiionet; the data contains 54 healthy people (age 28-76, average 61), and then denoise and preprocess the ECG signals, and extract the RRI signals from them , to obtain the RRI signal x(t); the specific method of denoising preprocessing is: since the ECG energy is mainly concentrated in 0-40Hz, the ECG signal is filtered through a 40Hz zero-phase FIR low-pass filter to eliminate high-frequency noise, and then passed through the middle value filter to remove baseline drift;

[0060] (2), using the RRI signal x(t) as the original signal, the minimum amount of data required by the origin...

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

A heart rate variability signal analysis method based on an extremum energy decomposition method, comprising obtaining an ECG signal in an unknown state at a given time and a given sampling frequency, and denoising the ECG signal to obtain an RRI signal x(t); using the RRI signal x(t) as an original signal, and decomposing the original signal x(t) into n extremum mode function components and one margin, the n extremum mode function components obtained by decomposing the original signal x(t) representing components of the original signal in different frequency bands; and determining, according to the n extremum mode function components, whether the RRI signal is an abnormal heart rate variability signal. According to the present invention, the RRI signal is analyzed using an extremum energy decomposition method, the original signal is decomposed into a plurality of components, i.e., an extremum component function, and energy of each component is calculated to obtain energy distribution thereof.

Description

technical field [0001] The invention relates to an electrocardiogram signal analysis, in particular to a heart rate variability signal analysis method based on an extreme value energy decomposition method. Background technique [0002] Physiological signals are generated by the interaction of multiple systems in a living body, and the time and intensity of different systems are different, resulting in the complexity of physiological signals in time and space. Heart rate variability (HRV) refers to the measurement of the variation in time between consecutive cardiac cycles, to be precise, it should be the variation in the measurement of the difference between consecutive normal P-P intervals. However, because the P wave is not as obvious as the R wave or the top of the P wave is sometimes broad and blunt, the research on the heart rate variability signal is usually replaced by the R-R interval signal (RRI) which is equal to the P-P interval. Studies have shown that HRV can b...

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): A61B5/0402A61B5/0205A61B5/00
CPCA61B5/0205A61B5/02405A61B5/0245A61B5/7203A61B5/7235A61B5/725A61B5/316A61B5/318
Inventor 宁新宝曾彭周作建姜晓东刘果王斌斌王华
Owner JIANGSU HUAKANG INFORMATION TECH CO LTD
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