Coronary heart disease self-diagnosis system based on electrocardiographic monitoring and back-propagation neural network

A technology of ECG monitoring and backpropagation, applied in biological neural network models, electrical digital data processing, special data processing applications, etc., can solve the problems of application scope and promotion limitations, failure to diagnose diseases, and remote monitoring, etc., to achieve The effect of reducing medical expenses and expanding medical coverage
CN102129509AInactive Publication Date: 2011-07-20ZHENGZHOU UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHENGZHOU UNIV
Publication Date
2011-07-20
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a coronary heart disease self-diagnosis system based on electrocardiographic monitoring and back-propagation neural network, comprising an electrocardiographic collection terminal and a hospital monitoring center computer system, wherein the electrocardiographic collection terminal is composed of an electrocardiographic monitoring collector and a data transmission module based on wired or wireless data transmission. By means of multi-scale features of wavelet transformation, the system of the invention completes the extraction of wave peak points and the detection of ST segment in different scale decomposition coefficients by adopting a quadratic spline wavelet transformation method, thus the electrocardiographic waveform of the clinical patient can be accurately extracted. On the basis of correctively extracting characteristic points, an electrocardiogram ST segment pattern recognition model is set up by using a BP (Back-Propagation) neutral network in order to successfully recognize the pattern of the ST segment, and the initial weight and the threshold of the BP neutral network are optimized by using genetic algorithm and DNA (deoxyribonucleic acid) algorithm, thereby problem that the BP neutral network is liable to fall into local optimum in the process of training is solved, and the pattern recognition of ST segment and the diagnosis of coronary heart disease in the manner of artificial experience before are replaced.
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Description

technical field

[0001] The invention relates to an electrocardiographic monitoring and self-diagnosis system for coronary heart disease, in particular to a self-diagnosing system for electrocardiographic monitoring and reverse propagating neural network through the Internet for electrocardiographic data transmission. Background technique

[0002] According to the analysis of the World Heart Federation, the mortality rate of coronary heart disease is much higher than that of other diseases, and it has become the main disease that threatens the safety of human life. Early diagnosis of coronary heart disease is extremely important for guiding treatment and evaluating prognosis. At present, the main diagnostic methods for coronary heart disease are coronary angiography and ECG (ie, electrocardiogram). Because coronary angiography is expensive and invasive, ECG based on noninvasive detection and analysis has become the most commonly used method. Among them, the important index ...

Claims

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