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In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This...
The electrocardiogram (ECG) is an essential clinical tool for the noninvasive assessment of cardiac function. Computational simulations of ECGs using bidomain models are considered the biophysically most detailed approach, but computational costs are significant. Alternatively, pseudo-bidomain formulations can be used, combining a monodomain model with an infrequent bidomain solve to obtain full extracellular...
We present generalizations of the previously published artificial models for generating abnormal cardiac rhythms to provide simulations of coupled cardiovascular (CV) signals with different beat morphologies. Using a joint dynamical formulation, we generate the normal morphologies of the cardiac cycle using a sum of Gaussian kernels, fitted to real CV recordings. The joint inter-dependencies of CV...
In this work we studied the improvement achieved by including information from the 12 ECG leads, in a previously developed classification model. This model includes features from the RR interval series and morphology descriptors calculated from the wavelet transform. The experiments were carried out in the INCART database, available in Physionet, and the generalization was corroborated in a private...
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