Research on diagnosing coronary heart disease using fuzzy adaptive resonance theory mapping neural networks

被引：0

作者：

Shi, Li ^{[1
]}

Sun, Zhifu ^{[1
]}

Li, Hui ^{[1
]}

Liu, Wei ^{[1
]}

机构：

[1] Zhengzhou Univ, Sch Elect Engn, Zhengzhou, Peoples R China

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7 | 2007年

关键词：

fuzzy ARTMAP; ST segment; coronary heart disease; BP network; ECG;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

ST segment is the most important diagnostic parameter for finding coronary heart disease (CHD). Based on ST segment which has been extracted from electrocardiogram (ECG) data with wavelet transform, we investigated the classification of five different shapes of ST segment using fuzzy adaptive resonance theory mapping (ARTMAP) neural networks. The proposed method was demonstrated by the data from the standard MIT/BIH ECG database. The results show that fuzzy ARTMAP could be used to distinguish the shapes of ST segment successfully.

引用

页码：1704 / 1706

页数：3

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