QRS wave starting point end point positioning method based on regularized least square regression learning

A technology of least squares and positioning method, which is applied in medical science, sensors, diagnostic recording/measurement, etc. It can solve the problems of baseline drift, difficult to make accurate analysis and judgment of signal quality, and low accuracy of QRS wave analysis and positioning. Achieve the effect of improving accuracy, good generalization and good applicability

Active Publication Date: 2016-11-02
ZHEJIANG HELOWIN MEDICAL TECH
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Problems solved by technology

At present, most of the mainstream methods for locating the start and end points of QRS waves on the market are only applicable to a certain type or several types of QRS waves. Figure 1.2 ), severe baselin

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  • QRS wave starting point end point positioning method based on regularized least square regression learning
  • QRS wave starting point end point positioning method based on regularized least square regression learning
  • QRS wave starting point end point positioning method based on regularized least square regression learning

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Embodiment Construction

[0019] The specific implementation of the present invention will be described in detail below with examples in combination with the technical scheme and the accompanying drawings.

[0020] The invention solves the problems of QRS wave detection and its start point and end point positioning in the electrocardiogram automatic diagnosis system. Based on the theory of regression learning and orthogonal decomposition of signals in Hilbert space, a series of detection methods, detection criteria and threshold parameters are constructed to detect and identify QRS waves, and locate the starting and ending positions of QRS waves. The specific implementation steps are as follows.

[0021] In the following discussion, if h represents a function, then h(x) represents the function value of the function h at point x; if h represents an array (integer or floating point type), then h[i] represents the i-th of the array h elements, where i is a non-negative integer.

[0022] 1. ECG signal con...

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Abstract

A QRS wave starting point end point positioning method based on regularized least square regression learning comprises the following steps: building a series of detection methods, detection criterions and threshold parameters according to function quadrature decomposition idea in the Hilbert space and the regularized least square regression learning algorithm, thus finally detecting the QRS wave and positioning the starting point and end point; carrying out inner product operation on an electrocardiosignal and a gauss function first order derived function so as to obtain an inner product sequence; selecting the reproducing kernel Hilbert space formed by the gauss kernel function as the approximation space of the regularized least square regression learning algorithm; using a real symmetric matrix square root decomposition method solving algorithm to obtain the novel inner product sequence.

Description

technical field [0001] The invention relates to the location measurement and analysis of the starting point and the ending point of the QRS wave in the dynamic electrocardiogram and the conventional electrocardiogram, specifically a method for locating the starting point and the ending point of the QRS wave based on regularized least squares regression learning, belonging to the technical field of electrocardiogram (ECG) automatic diagnosis and analysis. Background technique [0002] Electrocardiogram is one of the most widely used examination methods in clinical practice. It can help diagnose arrhythmia, myocardial ischemia, myocardial infarction, determine the location of infarction, determine the impact of drugs or electrolytes on the heart, and help implant artificial cardiac pacemakers, etc. . In addition, the tracing electrocardiogram is easy to operate and low in cost, and is especially suitable for use in areas with underdeveloped medical conditions. [0003] At pre...

Claims

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Application Information

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IPC IPC(8): A61B5/0402A61B5/0472A61B5/00A61B5/366
CPCA61B5/7203A61B5/7235A61B5/7271A61B5/316A61B5/366A61B5/318
Inventor 朱玉奎符灵建
Owner ZHEJIANG HELOWIN MEDICAL TECH
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