Ventricular premature beat intelligent analysis method based on abnormal characteristic values

A premature ventricular contraction and intelligent analysis technology, applied in signal pattern recognition, instrumentation, calculation, etc., can solve problems such as long calculation time, high complexity, and no consideration to solve data imbalance, so as to improve classification and recognition Effect

Active Publication Date: 2019-07-16
ZHENGZHOU UNIV
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Problems solved by technology

Although highly accurate methods have been developed for detecting PVC cardiac beats, their efficiency is usually accompanied by long computation time and high complexity
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  • Ventricular premature beat intelligent analysis method based on abnormal characteristic values
  • Ventricular premature beat intelligent analysis method based on abnormal characteristic values
  • Ventricular premature beat intelligent analysis method based on abnormal characteristic values

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Embodiment Construction

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0021] A method for intelligent analysis of premature ventricular beats based on abnormal eigenvalues, comprising the following steps:

[0022] 1) Signal preprocessing, use wavelet filter to denoise the original signal, and then locate the QRS complex wave through digital analysis of slope, amplitude and width, and finally perform centering on the R peak from the complete ECG signal Segment and extract a single heartbeat;

[0023] 2), feature extraction, select QRS complex w...

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Abstract

The invention relates to a ventricular premature beat intelligent analysis method based on abnormal characteristic values. The method comprises the following steps: 1) signal preprocessing: denoisingan original signal by using a wavelet filter, positioning a QRS composite wave through digital analysis of slope, amplitude and width, and finally segmenting and extracting a single heart beat from acomplete ECG signal by taking an R peak as a center; 2) feature extraction: selecting a QRS composite wave area, an RR interval and a QRS amplitude vector sum as feature parameters for input of a classifier; 3) model training: repeatedly and randomly extracting k samples from the original training sample set in a place-back manner through a self-service method resampling technology to generate a new training sample set, then generating M classification trees according to the self-service sample set to form a random forest, and determining a classification result of new data according to a score formed by the voting amount of the classification trees. The method has the advantages that abnormal signals with abnormal electrocardiosignal centrality are identified accurately, and classification is accurate.

Description

technical field [0001] The invention belongs to the technical field of heartbeat detection and classification, and in particular relates to an intelligent analysis method for premature ventricular beats based on abnormal characteristic values. Background technique [0002] Electrocardiogram (ECG) is a graph that records changes in the electrical activity of the heart in each cardiac cycle from the body surface, and it contains a wealth of basic functional and pathological information of the heart. Therefore, it has great significance in the evaluation of heart safety and evaluation of various treatment methods, and is currently an important means for the examination and diagnosis of various heart diseases such as arrhythmia. . Premature systole is the most common clinical arrhythmia, which refers to the heartbeat caused by the premature impulse from the ectopic pacemaker. According to the site of origin, it can be divided into four types: sinus, atrial, atrioventricular ju...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/02G06F2218/08G06F2218/12G06F18/24323
Inventor 李润川陈刚王宗敏谢天天张行进
Owner ZHENGZHOU UNIV
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