Electrocardiogram data pathological feature quantitative analysis method and device
A feature analysis and pathological technology, applied in the direction of diagnostic signal processing, diagnostic recording/measurement, medical science, etc., to achieve the effect of precise treatment and convenience
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Embodiment 1
[0046] Embodiment 1: The embodiment of the present invention mainly solves the quantitative extraction of cardiac dynamic pathological features inherent in the dynamic data of the nonlinear system of cardiac electrical activity, and further solves the problem of how to perform decision-making judgment and fusion of multiple extracted quantitative indicators.
[0047] An embodiment of the present invention provides a dynamic multi-pathological feature quantitative extraction method of the cardiac electrical activity system, including the following steps: preprocessing the cardiac electrical signal data, obtaining ECG vector data, and intercepting target band data; using adaptive system identification Methods The target band data is modeled, and then the obtained system dynamic model is multi-dimensionally visualized to obtain the dynamic data of the nonlinear system of cardiac electrical activity; the method of heterogeneity analysis is used to extract the intrinsic heart The qu...
Embodiment 2
[0074] Embodiment 2: This embodiment provides a dynamic multi-pathological feature quantitative extraction method of the cardiac electrical activity system, which is a separate implementation or a supplementary description to the extraction method described in Example 1, especially given Specific implementations of the different characteristic methods described therein. In this embodiment, the construction of the dynamic pathological characteristics of the nonlinear system of cardiac electrical activity is described in detail.
[0075] The construction of the pathological features described in this embodiment is to calculate the dynamic various pathological features of the nonlinear system of cardiac electrical activity, including the following two steps:
[0076] Step 1. Obtain the dynamic data of the nonlinear system of cardiac electrical activity
[0077] The nonlinear system dynamic modeling is carried out on the collected ECG data, so as to obtain the dynamic data of the...
Embodiment 3
[0095] Embodiment 3: As a separate embodiment or as a supplementary description to the schemes of Embodiments 1 and 2, Embodiment 3 focuses on the implementation of a single feature method, the detection and auxiliary judgment criteria of different cardiac electrical activity system dynamic pathological feature indicators , which exemplarily introduces an abnormal analysis method of cardiac electrical signals.
[0096] Include N clinically known heart healthy individuals (N>50) and M clinically known certain heart disease individuals (M>100) as the test sample population, collect the electrocardiogram of the test sample population, and use the existing technology (see CN107260161A) Obtain a dynamic map of the nonlinear system of cardiac electrical activity. Obtain the geometric feature values of all individuals by the geometric feature calculation method (according to the method described in step 2 (1) of Example 2), and carry out statistical classification based on probabil...
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