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

Identification method for premature beat in dynamic electrocardiogram

A dynamic electrocardiogram and identification method technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as poor accuracy and achieve the effect of avoiding influence

Active Publication Date: 2018-12-07
杭州质子科技有限公司
View PDF4 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of the poor accuracy of existing premature beat measurement methods, the purpose of the present invention is to provide a method for identifying supraventricular premature beats and ventricular premature beats in dynamic electrocardiograms. First, pre-classify dynamic cardiogram data based on supervised learning methods The normal sinus beat, supraventricular premature beat and ventricular premature beat are extracted, and then the extracted QRS complex wave of the normal sinus beat is used as a heart beat template, and finally the logic-based expert system is used to identify supraventricular premature beat and premature ventricular beat

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
  • Identification method for premature beat in dynamic electrocardiogram
  • Identification method for premature beat in dynamic electrocardiogram

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention will be further described below in conjunction with the accompanying drawings.

[0023] refer to figure 1 and figure 2 , a method for identifying premature beats in a dynamic electrocardiogram. First, the training data containing nine features is extracted from the ECG signal database marked with the existing heartbeat type, and then the corresponding features are also extracted from the dynamic electrocardiographic data to be detected to form the test data. The supervised learning classification algorithm pre-classifies the test data into sinus beats, premature supraventricular beats, and premature ventricular beats, and then uses an expert system based on similarity measure, ECG morphology, and RR interval to judge supraventricular premature beats and premature ventricular beats .

[0024] refer to figure 2 , the above-mentioned steps for judging supraventricular premature beats and ventricular premature beats based on the expert system, the...

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 relates to an identification method for the premature beat in a dynamic electrocardiogram. The method comprises the following steps that 1) according to the detected position of the heartbeat, an inputFeature is extracted; 2) inputFeatures of the sinus heartbeat, the supraventricular premature beat heartbeat and the ventricular premature beat heartbeat are extracted from an electrocardiosignal database labelled with the known heartbeat type and merged into training data; 3) corresponding inputFeatures are extracted from all heartbeats of the dynamic electrocardiogram to be analyzed and merged into test Data; 4) a supervised learning algorithm is adopted for pre-classifying the test Data, the corresponding heartbeat types are output, and position information of the sinus heartbeat is extracted; 5) a certain number of pre-classified sinus heartbeats are selected and averaged, and a template of a sinus QRS composite wave is obtained; 6) by adopting an expert system based onsimilarity measurement, ECG forms and RR intervals, the supraventricular premature beat and the ventricular premature beat are judged. The method is suitable for identification of the ventricular premature beat and the supraventricular premature beat of long-time electrocardiogram data of the dynamic electrocardiogram and effectively assists doctors in making related diagnosis quickly.

Description

technical field [0001] The invention relates to the technical field of automatic auxiliary detection of dynamic electrocardiogram, in particular to a method for identifying supraventricular premature beats and ventricular premature beats in dynamic electrocardiogram. Background technique [0002] Holter is a kind of surface electrocardiogram recorded continuously for a long time. It contains more abundant physiological information of human body than conventional electrocardiogram, and can reflect and monitor the physical condition of patients more objectively. But at the same time, due to its long-term nature, the dynamic electrocardiogram contains a large number of heart beats and complicated types, which greatly increases the workload of doctors, which makes the automatic auxiliary detection technology of dynamic electrocardiography increasingly important. [0003] Premature contractions, also known as premature contractions, include premature atrial contractions, prematur...

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): A61B5/0402A61B5/0472A61B5/366
CPCA61B5/7267A61B5/366A61B5/318
Inventor 陈蒙钟一舟宓城
Owner 杭州质子科技有限公司
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