A method for abnormal ECG tensor analysis in telemedicine

Abstract

The invention discloses a method for analyzing abnormal electrocardiogram tension for remote medical care. The method comprises the following steps of firstly, collecting a large amount of standard 12-lead electrocardiogram data in a remote method; then, converting the electrocardiogram into high-dimension tension electrocardiogram data by a short-time Fourier transform; directly using the high-dimension tension electrocardiogram data as a feature, and extracting electrocardiogram features directly being used for classification by an feature extraction and feature dimension reduction algorithm through directly using the tension data as the input. Because the method is based on a TTV (transit timing variable) transform principle, the features based on vector storage can be obtained, and then the vector features are classified by a SVM (support vector machine) classifying method. The method has the advantages that the tension electrocardiogram data are directly used as the input, the structure information of multi-lead electrocardiogram is fully utilized, the defect of non-precise data ton single analysis of the original single-lead electrocardiogram is eliminated, and the effectivity of the electrocardiogram analysis is realized.

Description

technical field [0001] The invention relates to a feature extraction and auxiliary classification method for multi-lead tensor electrocardiogram data aimed at a remote electrocardiogram diagnosis platform. Background technique [0002] This system is based on the Internet of Things technology and uses the remote ECG diagnosis platform to extend the high-quality medical services of Shanghai's tertiary hospitals to remote county-level and even community-level medical centers. A personalized service system is designed to improve the usability and efficiency of the telemedicine and health monitoring platform. Use the Internet of Things to build a remote medical cloud service platform, and establish a remote ECG diagnosis service demonstration in grassroots medical units. The construction of telemedicine cloud services mainly includes key technologies such as medical information collection, transmission, data processing, and feedback diagnosis. At present, the ECG signal acquis...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the inefficiency caused by the decentralization of the existing decentralized ECG diagnosis system, and at the same time aim at the inaccurate defects based on the original single-lead ECG analysis, and propose a method for multi-lead ECG analysis. Electrocardiographic analysis method for tensor ECG data

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