Primitive coding of structural ECG features

被引：7

作者：

Koski, A

机构：

[1] University of Turku, Department of Computer Science, 20520 Turku

来源：

PATTERN RECOGNITION LETTERS | 1996年 / 17卷 / 11期

关键词：

electrocardiograms (EGG); learning vector quantization (LVQ); self-organising map (SOM); syntactic pattern recognition;

D O I：

10.1016/0167-8655(96)00079-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a hybrid of self-organizing feature map and learning vector quantization and a rule base classification for the extraction of structural primitives of ECG signals is presented. Structural primitives are the elementary building blocks of an ECG signal and they are used in the syntactic recognition and analysis of the signal. The analysis based on the coding by the codebook vectors and slope rules was as successful as the analysis of the manually labelled test set.

引用

页码：1215 / 1222

页数：8

共 26 条

[1] CONTRIBUTION TO THE AUTOMATIC PROCESSING OF ELECTROCARDIOGRAMS USING SYNTACTIC METHODS [J].