Parametric Modeling for Estimating Abnormal Intra-QRS Potentials in Signal-Averaged Electrocardiograms: A Subspace Identification Approach

Author(s)

Jose A. Ramos, Nova Southeastern UniversityFollow
Paulo Lopes dos Santos

Document Type

Article

Publication Title

IFAC Proceedings Volumes

Event Date/Location

Brussels, Belgium

ISSN

1474-6670

Publication Date

7-2012

Abstract

This paper addresses the detection and classification of low amplitude signals within the QRS complex of the signal-averaged electrocardiogram. Linear and bilinear Kalman filter models are fitted using the subspace system identification family of algorithms. If the residuals from the models are a white noise process, then anything that cannot be modeled with the state-space models will show up in the residuals as low amplitude signal + noise. Diagnostic tests and analysis on the residuals will then lead to detection and classification of abnormalities in the intra-QRS complex. The end result is a diagnostic tool to aid the physician.

DOI

10.3182/20120711-3-BE-2027.00402

Volume

45

Issue

16

First Page

565

Last Page

570

NSUWorks Citation

Ramos, Jose A. and Lopes dos Santos, Paulo, "Parametric Modeling for Estimating Abnormal Intra-QRS Potentials in Signal-Averaged Electrocardiograms: A Subspace Identification Approach" (2012). CCE Faculty Articles. 409.
https://nsuworks.nova.edu/gscis_facarticles/409