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Model-driven processing of cardio-respiratory data using dynalet transform (Preprint)


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 This paper proposes a new data processing approach tailored to a model of the complex biological system studied. We will take as example the cardiac system made of a stimulator (represented for the sake of simplicity by the sinoatrial node), controlled by the respiratory oscillator, synchronizing a collection of sinoatrial node myocytes (pacemaker cells) and propose a mathematical model of the global system built from two van der Pol differential systems historically proposed for giving a first approximation of the cardiac and the respiratory activity. Then, we develop the observed cardiac signal on a functional base of approximate analytic solutions of the model. Finally, we propose perspectives to use it in the early detection of the drowsiness.
