ECG parametric modeling based on signal dependent orthogonal transform
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Date
2014-07-02
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
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 nonlinear 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 MITBIH 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.
Description
Keywords
Electrocardiography, Transforms, Heartbeat, Vectors, Computational modeling, Biological system modeling, Parametric statistics
Citation
Baali, H., Akmeliawati, R., Salami, M. J. E., Khorshidtalab, A., & Lim, E. (2014). ECG parametric modeling based on signal dependent orthogonal transform. IEEE Signal Processing Letters, 21(10), 1293-1297.