Identification of cardiac arrhythmias using a damped exponential-predominant frequency algorithm

Szi Wen Chen; Peter M. Clarkson

Identification of cardiac arrhythmias using a damped exponential-predominant frequency algorithm

Szi Wen Chen^*
, Peter M. Clarkson

^*Corresponding author for this work

Ohio State University

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

1 Scopus citations

Abstract

In this paper, we describe a new approach for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) based on a damped exponential (DE) modeling algorithm. Classification is achieved by simple linear separation applied to a novel feature, dubbed predominant frequency (PF), derived from the DE model. Tests conducted using 70 episodes drawn from the MIT-BIH malignant arrhythmia database produced total predictive accuracy exceeding 98%.

Original language	English
Pages (from-to)	181-182
Number of pages	2
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	17
Issue number	1
State	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference. Part 2 (of 2) - Montreal, Can Duration: 20 09 1995 → 23 09 1995

Cite this

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title = "Identification of cardiac arrhythmias using a damped exponential-predominant frequency algorithm",

abstract = "In this paper, we describe a new approach for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) based on a damped exponential (DE) modeling algorithm. Classification is achieved by simple linear separation applied to a novel feature, dubbed predominant frequency (PF), derived from the DE model. Tests conducted using 70 episodes drawn from the MIT-BIH malignant arrhythmia database produced total predictive accuracy exceeding 98\%.",

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AU - Clarkson, Peter M.

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AB - In this paper, we describe a new approach for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) based on a damped exponential (DE) modeling algorithm. Classification is achieved by simple linear separation applied to a novel feature, dubbed predominant frequency (PF), derived from the DE model. Tests conducted using 70 episodes drawn from the MIT-BIH malignant arrhythmia database produced total predictive accuracy exceeding 98%.

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M3 - 会议文章

AN - SCOPUS:0029429594

SN - 0589-1019

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EP - 182

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

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T2 - Proceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference. Part 2 (of 2)

Y2 - 20 September 1995 through 23 September 1995

ER -

Identification of cardiac arrhythmias using a damped exponential-predominant frequency algorithm

Abstract

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