e-journal

Multiscale Adaptive Basis Function Modeling of Spatiotemporal Vectorcardiogram Signals

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Abstract—Mathematical modeling of cardiac electrical signals facilitates the simulation of realistic cardiac electrical behaviors, the evaluation of algorithms, and the characterization of underlying space-time patterns. However, there are practical issues pertinent to model efficacy, robustness, and generality. This paper presents a multiscale adaptive basis function modeling approach tocharacterizenotonlytemporalbutalsospatialbehaviorsofvectorcardiogram (VCG) signals. Model parameters are adaptively estimated by the “best matching” projections of VCG characteristicwavesontoadictionaryofnonlinearbasisfunctions.Themodel performance is experimentally evaluated with respect to the number of basis functions, different types of basis function (i.e., Gaussian, Mexican hat, customized wavelet, and Hermitian wavelets), and various cardiac conditions, including 80 healthy controls and differentmyocardialinfarctions(i.e.,89inferior,77anterior-septal, 56 inferior-lateral, 47 anterior, and 43 anterior-lateral). Multiway analysis of variance shows that the basis function and the model complexity have significant effects on model performances while cardiac conditions are not significant. The customized wavelet is found to be an optimal basis function for the modeling of spacetime VCG signals. The comparison of QT intervals shows small relative errors (

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Ketersediaan

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS., 2013

Deskripsi Fisik

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 2, MARCH 2013 p. 484-492

Bahasa

English

ISBN/ISSN

2168-2194

Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

REKAYASA BIOMEDIS

Info Detail Spesifik

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Pernyataan Tanggungjawab

Gang Liu and Hui Yang

Versi lain/terkait

Lampiran Berkas

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