Myocardial ischemia detection using Hidden Markov principal component analysis

Mauricio Alexánder Alvarez López; R. Henao; A. Orozco

doi:10.1007/978-3-540-74471-9_24

Myocardial ischemia detection using Hidden Markov principal component analysis

Mauricio Alexánder Alvarez López, R. Henao, A. Orozco

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

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. © Springer-Verlag Berlin Heidelberg 2007.

Original language	English (US)
Title of host publication	IFMBE Proceedings
Publisher	Springer Verlagservice@springer.de
Pages	99-103
Number of pages	5
ISBN (Print)	9783540744702
DOIs	https://doi.org/10.1007/978-3-540-74471-9_24
State	Published - Jan 1 2008
Externally published	Yes

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Generated from Scopus record by KAUST IRTS on 2023-02-15

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10.1007/978-3-540-74471-9_24

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title = "Myocardial ischemia detection using Hidden Markov principal component analysis",

abstract = "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. {\textcopyright} Springer-Verlag Berlin Heidelberg 2007.",

author = "{Alvarez L{\'o}pez}, {Mauricio Alex{\'a}nder} and R. Henao and A. Orozco",

note = "Generated from Scopus record by KAUST IRTS on 2023-02-15",

year = "2008",

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TY - GEN

T1 - Myocardial ischemia detection using Hidden Markov principal component analysis

AU - Alvarez López, Mauricio Alexánder

AU - Henao, R.

AU - Orozco, A.

N1 - Generated from Scopus record by KAUST IRTS on 2023-02-15

PY - 2008/1/1

Y1 - 2008/1/1

N2 - 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. © Springer-Verlag Berlin Heidelberg 2007.

AB - 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. © Springer-Verlag Berlin Heidelberg 2007.

UR - http://link.springer.com/10.1007/978-3-540-74471-9_24

UR - http://www.scopus.com/inward/record.url?scp=75149132126&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-74471-9_24

DO - 10.1007/978-3-540-74471-9_24

M3 - Conference contribution

SN - 9783540744702

SP - 99

EP - 103

BT - IFMBE Proceedings

PB - Springer Verlagservice@springer.de

ER -

Myocardial ischemia detection using Hidden Markov principal component analysis

Abstract

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