Myocardial Ischemia Detection using Hidden Markov Principal Component Analysis

被引：0

作者：

Alvarez, M. ^{[1
]}

Henao, R. ^{[2
]}

Orozco, A. ^{[1
]}

机构：

[1] Univ Tecnol Pereira, Program Elect Engn, La Julita, Pereira, Colombia

[2] Univ Tecnol Pereira, Sch Elect Engn, Pereira, Colombia

来源：

IV LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING 2007, BIOENGINEERING SOLUTIONS FOR LATIN AMERICA HEALTH, VOLS 1 AND 2 | 2008年 / 18卷 / 1,2期

关键词：

Hidden Markov Model; Principal Component Analysis; Myocardial Ischemia;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper introduces a new temporal version of Principal Component Analysis by using a Hidden Markov Model in order to obtain optimized representations of observed data through time. The novelty of the proposed method consists mainly in the way in which a static dimensionality reduction technique has been combined with a classic mixture model in time, to enhance the capabilities of dimensionality reduction and classification of myocardial ischemia data. Experimental results show improvements in classification accuracies even with highly reduced representations.

引用

页码：99 / +

页数：3

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