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

Ventricular fibrillation detection method, storage medium and device

A detection method and technology for ventricular fibrillation, applied in the field of signal processing, to achieve the effect of accurate identification and improvement of the success rate of defibrillation

Active Publication Date: 2019-01-15
鹤为科技(北京)有限公司
View PDF3 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of this, the present invention provides a ventricular fibrillation detection method, storage medium and device to solve the problem of manual detection of ventricular fibrillation

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
  • Ventricular fibrillation detection method, storage medium and device
  • Ventricular fibrillation detection method, storage medium and device
  • Ventricular fibrillation detection method, storage medium and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1 Embodiment 2

[0062] Example as Figure 5 shown.

[0063] Step 201: sequentially extract the RR intervals in the ECG signal data, and store the newly extracted RR intervals into the newly recorded RR interval sequence;

[0064] Step 202: When the newly recorded RR interval sequence is not empty, take out the RR intervals in the newly recorded RR interval sequence sequentially, and when the RR intervals taken out continuously within the first preset duration are in the abnormal range, the probability is greater than the second preset value, execute step 203;

[0065] Step 203: Identify the waveform characteristics of the ECG signal data for the first preset time period. If the waveform characteristics conform to the preset oscillation state, execute step 103; otherwise, determine that no ventricular fibrillation is detected, and return to step 202.

[0066] Step 103: Calculate the complexity of the ECG signal data for the first preset duration, and determine whether the complexity is great...

Embodiment 3

[0080] Embodiment three and embodiment four

[0081] Embodiment three such as Figure 7 shown.

[0082] Step 301: sequentially extract the waveform features in the ECG signal data, and store the newly extracted waveform features into the newly recorded waveform feature sequence;

[0083] Step 302: When the newly recorded waveform feature sequence is not empty, sequentially extract the waveform features in the newly recorded waveform feature sequence, and when the continuously extracted waveform features within the first preset duration conform to the preset oscillation state, then perform step 303;

[0084] Step 303: Extract the RR interval of the intracardiac signal data of the first preset time length, if the probability of the RR interval being in the abnormal range is greater than the second preset value, then execute step 103, otherwise it is determined that no ventricular fibrillation is detected, and return to step 302 .

[0085] Step 103: Calculate the complexity of...

Embodiment 4

[0086] Embodiment four such as Figure 8 shown.

[0087] Step 301-2: Sequentially extract the waveform features in the ECG signal data, store the newly extracted waveform features into the waveform feature sequence, and the newly extracted waveform features are unanalyzed waveform features in the waveform feature sequence;

[0088] Step 302-2: When the unanalyzed waveform features in the waveform feature sequence are not empty, read the unanalyzed waveform features sequentially, and convert the unanalyzed waveform features into analyzed waveform features after being read. If the waveform characteristics read continuously within the preset time period conform to the preset oscillation state, then step 303-2 is executed;

[0089] Step 303-2: Extract the RR interval of the ECG signal data of the first preset time length, if the probability of the RR interval being in the abnormal range is greater than the second preset value, then perform step 103, otherwise it is determined tha...

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 $$ fibrillation detection method is provided and includes a step 101 of sequentially extracting characteristic information of electrocardiogram signal data, and executing step 103 when that characteristic information continuously extracted in a first preset time length conforms to a first judgment condition, wherein the first judgment condition is a distinctive characteristic of the characteristic information at the time of ventricular fibrillation and at the time when ventricular fibrillation does not occur; a step 103 of calculating that complexity of the first preset time length ECG signal data, judging whet the complexity is greater than the first preset value, and if so, judging that ventricular fibrillation is detected; otherwise, judging that no ventricular fibrillation is detected. The method can automatically and quickly judge whether ventricular fibrillation occurs or not based on the collected data, so as to improve the success rate of defibrillation.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a method for detecting ventricular fibrillation, a storage medium and a device. Background technique [0002] Ventricular fibrillation (VF, referred to as ventricular fibrillation) is a serious cardiovascular disease, which is caused by human factors such as coronary heart disease and myocardial infarction or external factors such as surgery and drug poisoning. When ventricular fibrillation occurs, the patient is usually unconscious, pulseless, and bloodless, and is at high risk, which may threaten the patient's life at any time. [0003] When a patient has ventricular fibrillation, timely detection and electric shock defibrillation are currently recognized as an important means of treatment for the patient. If defibrillation can be implemented within 1 minute of ventricular fibrillation, the success rate of defibrillation can be close to 100%. After 5 minutes of ventricular fib...

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): A61B5/0402A61B5/046A61B5/361
CPCA61B5/361A61B5/318
Inventor 王金石
Owner 鹤为科技(北京)有限公司
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