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.