NDLI: Time series prediction using parametric models and multilayer perceptrons: case study on heart signals

Content Provider	IEEE Xplore Digital Library
Author	El Dajani, R. Miquel, M. Maison-Blanche, P. Rubel, P.
Copyright Year	2003
Description	Author affiliation: Lab. d'Ingenierie des Syst. d'Inf., Inst. Nat. des Sci. Appliquees de Lyon, Villeurbanne, France (El Dajani, R.; Miquel, M.)
Abstract	Physiological signals are usually patient specific, and they are difficult to predict, especially for the cardiovascular system. New methods capable to be adapted to each case and to learn the singular behavior of heart functions should be developed to support physicians in their decisionmaking. One of the most widely studied relations is the QT-RR one, between the total duration of the ventricle activation and inactivation, and the heart rate. In the past, different studies were made to approach this relation in the steady state. In this paper, a new method for modeling and predicting the transient dynamic behavior of QT interval in relation to changing RR intervals is presented using parametric models and multilayer perceptrons (MLP).
Sponsorship	IEEE Signal Process, Soc
File Size	272307
File Format	PDF
ISBN	0780376633
ISSN	15206149
DOI	10.1109/ICASSP.2003.1202481
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parametric statistics Multilayer perceptrons Computer aided software engineering Heart rate interval Steady-state Predictive models Electrocardiography Heart rate Heart beat History
Content Type	Text
Resource Type	Article

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