Automatic classification method for ST-segment evaluation patterns in electrocardiograph signals

An electrocardiographic signal and automatic classification technology, applied in the field of biomedical engineering, can solve the problems of inaccurate ST segment morphological classification and inaccurate ST segment positioning, achieve simple and accurate classification, avoid noise interference, and ensure the effect of accuracy

Active Publication Date: 2015-06-03
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Problems solved by technology

[0004] In order to avoid the shortcomings of the above-mentioned prior art, the present invention provides a method for automatically classifying the shape of the ST segment in the ECG signal based on the curvature scale space, in order to provide a new reference for the clinical automatic detection of myocardial ischemia. It is a technical problem of the inaccurate positioning of the ST segment by the computer in clinical practice and the inaccurate classification of the shape of the ST segment.

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  • Automatic classification method for ST-segment evaluation patterns in electrocardiograph signals
  • Automatic classification method for ST-segment evaluation patterns in electrocardiograph signals
  • Automatic classification method for ST-segment evaluation patterns in electrocardiograph signals

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[0047] In order to make the above objects, features and advantages of the present invention more comprehensible, the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0048] Such as figure 1 As shown, in this embodiment, the ST segment is first pre-classified into five types, including: horizontal type, upward slope type, downward slope type, concave type and convex type;

[0049] Such as figure 2 As shown, the method for classifying ST segment morphology based on the curvature scale space in this embodiment is carried out in the following steps:

[0050] 1. Use the time variable t to express the original ECG signal as O(t)=(s(t),v(t)), and use the Gaussian low-pass filter (LPF) to obtain the ECG smooth signal C(t,σ)=( S(t,σ),V(t,σ)), such as image 3 as shown in (a);

[0051] 2. If image 3 As shown in (b), use the formula (1) to calculate the curvature valu...

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Abstract

The invention provides an automatic classification method for ST-segment evaluation patterns in electrocardiograph (ECG) signals. The automatic classification method is characterized by comprising the following steps: collecting the lead ECG signals of a human body; classifying the ST-segment evaluation patterns in the ECG signals into horizontal type, upper inclined type, lower inclined type, concave type and convex type; utilizing the multi-scale analysis method of curvature scale space technology to position ST-segment and obtain the point corresponding to the maximum value of the absolute value of the curvature in the ST-segment, namely the maximum point of the bending degree of the ST-segment; according to the characteristic of the curvature, utilizing the maximum point of the bending degree in the ST-segment to judge the ST-segment evaluation patterns. By introduction of the curvature scale space method, the influence of noise is effectively reduced, the ST-segment evaluation patterns can be accurately identified, and the method has an important use value for early warning of myocardial ischemia.

Description

technical field [0001] The invention relates to the technical field of biomedical engineering, in particular to an automatic classification method for ST segment morphology used for early warning of myocardial ischemia. Background technique [0002] Coronary stenosis or occlusion caused by coronary atherosclerosis is the main and most common cause of myocardial ischemia, and severe myocardial ischemia and hypoxia can lead to coronary heart disease. Myocardial ischemia seriously endangers the health of middle-aged and elderly people, and the average prevalence rate in my country is about 6.49%. However, with the improvement of people's living standards in our country, atherosclerosis gradually presents a younger trend, leading to an increase in the prevalence of myocardial ischemia year by year, seriously endangering the health of our people. Therefore, accurate and effective detection of myocardial ischemic changes has important clinical significance. [0003] At present, ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62A61B5/0452
Inventor 张永亮黎承涛叶骏何子军胡福松彭文超吴璋洋马祖长孙怡宁
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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