Parametrical modelling of a premature ventricular contraction ECG beat: Comparison with the normal case

Authors:
Lina El Khansa;Amine Naït-Ali
Affiliations:
Laboratoire Images, Signaux et Systèmes Intelligents (LISSI EA 3956), Université Paris XII Val de Marne, 61 avenue du Général de Gaulle, 94010 Créteil, France;Laboratoire Images, Signaux et Systèmes Intelligents (LISSI EA 3956), Université Paris XII Val de Marne, 61 avenue du Général de Gaulle, 94010 Créteil, France
Venue:
Computers in Biology and Medicine
Year:
2007

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Abstract

The aim of this paper is to analyse a parametrical Gaussian kernel based model. The proposed model is tested on two types of electrocardiogram (ECG) beats, the normal case beat and the premature ventricular contraction (PVC) one. Basically, the model is constituted of N Gaussians where their corresponding parameters are estimated by optimising a specific criterion. The modelling technique has been validated using MIT/BIH databases. As a result of this study, we show that a normal beat can be modelled using 18 parameters and only 15 parameters are needed to reconstruct the PVC one.