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Parametric modeling in estimating abnormal intra-QRS potentials in signal-averaged electrocardiograms: A subspace identification approach
Title
Parametric modeling in estimating abnormal intra-QRS potentials in signal-averaged electrocardiograms: A subspace identification approach
Type
Article in International Conference Proceedings Book
Year
2012
Authors
Ramos, JA
(Author)
Other
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Without AUTHENTICUS
Without ORCID
P. Lopes dos Santos
(Author)
FEUP
Conference proceedings International
Pages: 565-570
Universite Libre de Bruxelles
Bruxelles, 11 July 2012 through 13 July 2012
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Other information
Authenticus ID:
P-008-6FW
Abstract (EN):
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. © 2012 IFAC.
Language:
English
Type (Professor's evaluation):
Scientific
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