A reconstructed phase space approach for distinguishing ischemic from non-ischemic ST changes using Holter ECG data

Michael W. Zimmerman; Richard J. Povinelli; M. T. Johnson; K. M. Ropella

doi:10.1109/cic.2003.1291136

A reconstructed phase space approach for distinguishing ischemic from non-ischemic ST changes using Holter ECG data

Michael W. Zimmerman, Richard J. Povinelli, M. T. Johnson, K. M. Ropella

Research output: Contribution to journal › Conference article › peer-review

21 Scopus citations

Abstract

A method for the classification of ST events through the use of reconstructed phase spaces of the ECG signal is proposed. There is a clinical need for the creation of an automated system for classification of ST events as ischemic or non-ischemic as existing ischemia detection methods are expensive, invasive, or both. The algorithm proposed herein attempts to classify events using the 16 beats surrounding a given ST event. The ST segment and T wave of each of these beats is embedded in a phase space and then modelled and classified through the use of Gaussian Mixture Models (GMM). Using ten-fold cross validation of available training data the sensitivity and specificity were 81.0% and 88.1% respectively.

Original language	English
Pages (from-to)	243-246
Number of pages	4
Journal	Computers in Cardiology
Volume	30
DOIs	https://doi.org/10.1109/cic.2003.1291136
State	Published - 2003
Event	Computers in Cardiology 2003 - Thessaloniki Chalkidiki, Greece Duration: Sep 21 2003 → Sep 24 2003

ASJC Scopus subject areas

Computer Science Applications
Cardiology and Cardiovascular Medicine

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10.1109/cic.2003.1291136

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title = "A reconstructed phase space approach for distinguishing ischemic from non-ischemic ST changes using Holter ECG data",

abstract = "A method for the classification of ST events through the use of reconstructed phase spaces of the ECG signal is proposed. There is a clinical need for the creation of an automated system for classification of ST events as ischemic or non-ischemic as existing ischemia detection methods are expensive, invasive, or both. The algorithm proposed herein attempts to classify events using the 16 beats surrounding a given ST event. The ST segment and T wave of each of these beats is embedded in a phase space and then modelled and classified through the use of Gaussian Mixture Models (GMM). Using ten-fold cross validation of available training data the sensitivity and specificity were 81.0% and 88.1% respectively.",

author = "Zimmerman, {Michael W.} and Povinelli, {Richard J.} and Johnson, {M. T.} and Ropella, {K. M.}",

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AU - Povinelli, Richard J.

AU - Johnson, M. T.

AU - Ropella, K. M.

PY - 2003

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N2 - A method for the classification of ST events through the use of reconstructed phase spaces of the ECG signal is proposed. There is a clinical need for the creation of an automated system for classification of ST events as ischemic or non-ischemic as existing ischemia detection methods are expensive, invasive, or both. The algorithm proposed herein attempts to classify events using the 16 beats surrounding a given ST event. The ST segment and T wave of each of these beats is embedded in a phase space and then modelled and classified through the use of Gaussian Mixture Models (GMM). Using ten-fold cross validation of available training data the sensitivity and specificity were 81.0% and 88.1% respectively.

AB - A method for the classification of ST events through the use of reconstructed phase spaces of the ECG signal is proposed. There is a clinical need for the creation of an automated system for classification of ST events as ischemic or non-ischemic as existing ischemia detection methods are expensive, invasive, or both. The algorithm proposed herein attempts to classify events using the 16 beats surrounding a given ST event. The ST segment and T wave of each of these beats is embedded in a phase space and then modelled and classified through the use of Gaussian Mixture Models (GMM). Using ten-fold cross validation of available training data the sensitivity and specificity were 81.0% and 88.1% respectively.

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JO - Computers in Cardiology

JF - Computers in Cardiology

T2 - Computers in Cardiology 2003

Y2 - 21 September 2003 through 24 September 2003

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A reconstructed phase space approach for distinguishing ischemic from non-ischemic ST changes using Holter ECG data

Abstract

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