ECG Identification of Arrhythmias by using an Associative Petri Net

被引：0

作者：

Shih, Dong-Her ^{[1
]}

Chiang, Hsiu-Sen ^{[2
]}

Shih, Ming-Hung ^{[3
]}

机构：

[1] Natl Yunlin Univ Sci & Technol, Dept Informat Management, Touliu, Yunlin, Taiwan

[2] Natl Taichung Univ Technol, Dept Management Informat, Taichung 404, Taiwan

[3] Univ Cincinnati, Dept Elect & Elect Engn, Cincinnati, OH 45221 USA

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER) | 2013年

关键词：

Electrocardiography Arrhythmia; Associative Petri Net; Association rule; Reasoning; NEURAL-NETWORK; MODEL;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this study, classifier by using associative Petri net for personalized ECG arrhythmias pattern identification is proposed. Association production rules and reasoning algorithm of APN are created for ECG arrhythmias detection. The performance of our approach compares well with previously reported results and could be a part of monitoring system for the detection of ECG arrhythmias.

引用

页数：3

共 8 条

[1] A support vector machine classifier algorithm based on a perturbation method and its application to ECG beat recognition systems [J].