ECG parametric modeling based on signal dependent orthogonal transform

In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse respon...

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Main Authors:	Baali, Hamza, Akmeliawati, Rini, Salami, Momoh Jimoh Eyiomika, Khorshidtalab, Aida, E., Lim
Format:	Article
Language:	English
Published:	IEEE 2014
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/1/06847763_SPL.pdf

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spelling	iium-371552018-05-24T07:55:28Z http://irep.iium.edu.my/37155/ ECG parametric modeling based on signal dependent orthogonal transform Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim TK Electrical engineering. Electronics Nuclear engineering In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse response matrix of the LPC filter. The resulting spectral coefficients vector would be concentrated, leading to an approximation to a sum of exponentially damped sinusoids (EDS). A two-stage procedure is then used to estimate the model parameters. The Prony’s method is first employed to obtain initial estimates of the model, while the Levenberg–Marquardt (LM) method is then applied to solve the non-linear least-square optimization problem. The ECG signal is reconstructed using the EDS parameters and the linear prediction coefficients via the inverse transform. The merit of the proposed modeling technique is illustrated on the clinical data collected from the MIT-BIH database including all the arrhythmias classes that are recommended by the Association for the Advancement of Medical Instrumentation (AAMI). For all the tested ECG heartbeats, the average values of the percent root mean square difference (PRDs) between the actual and the reconstructed signals were relatively low, varying between a minimum of 3.1545% for Premature Ventricular Contractions (PVC) class and a maximum of 10.8152% for Nodal Escape (NE) class. IEEE 2014-10 Article PeerReviewed application/pdf en http://irep.iium.edu.my/37155/1/06847763_SPL.pdf Baali, Hamza and Akmeliawati, Rini and Salami, Momoh Jimoh Eyiomika and Khorshidtalab, Aida and E., Lim (2014) ECG parametric modeling based on signal dependent orthogonal transform. IEEE Signal Processing Letters, 21 (10). pp. 1293-1297. ISSN 1070-9908 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6847763 10.1109/LSP.2014.2332425
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim ECG parametric modeling based on signal dependent orthogonal transform
description	In this letter, we propose a parametric modeling technique for the electrocardiogram (ECG) signal based on signal dependent orthogonal transform. The technique involves the mapping of the ECG heartbeats into the singular values (SV) domain using the left singular vectors matrix of the impulse response matrix of the LPC filter. The resulting spectral coefficients vector would be concentrated, leading to an approximation to a sum of exponentially damped sinusoids (EDS). A two-stage procedure is then used to estimate the model parameters. The Prony’s method is first employed to obtain initial estimates of the model, while the Levenberg–Marquardt (LM) method is then applied to solve the non-linear least-square optimization problem. The ECG signal is reconstructed using the EDS parameters and the linear prediction coefficients via the inverse transform. The merit of the proposed modeling technique is illustrated on the clinical data collected from the MIT-BIH database including all the arrhythmias classes that are recommended by the Association for the Advancement of Medical Instrumentation (AAMI). For all the tested ECG heartbeats, the average values of the percent root mean square difference (PRDs) between the actual and the reconstructed signals were relatively low, varying between a minimum of 3.1545% for Premature Ventricular Contractions (PVC) class and a maximum of 10.8152% for Nodal Escape (NE) class.
format	Article
author	Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim
author_facet	Baali, Hamza Akmeliawati, Rini Salami, Momoh Jimoh Eyiomika Khorshidtalab, Aida E., Lim
author_sort	Baali, Hamza
title	ECG parametric modeling based on signal dependent orthogonal transform
title_short	ECG parametric modeling based on signal dependent orthogonal transform
title_full	ECG parametric modeling based on signal dependent orthogonal transform
title_fullStr	ECG parametric modeling based on signal dependent orthogonal transform
title_full_unstemmed	ECG parametric modeling based on signal dependent orthogonal transform
title_sort	ecg parametric modeling based on signal dependent orthogonal transform
publisher	IEEE
publishDate	2014
url	http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/ http://irep.iium.edu.my/37155/1/06847763_SPL.pdf
first_indexed	2023-09-18T20:53:18Z
last_indexed	2023-09-18T20:53:18Z
_version_	1777410138160758784

ECG parametric modeling based on signal dependent orthogonal transform

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