Métodos númericos aplicados a modelos complexos da fisiologia de células cardíacas

Abstract

The computational modeling of cardiac physiology is an important tool for development of new techniques of treatment and diagnosis of cardiac disease. The research on realistic cellular models has encouraged the usage of Markov Chains for modeling cell substructures, i.g. the ionic channels that permeate the cell membrane. In this work, we combinate different numerical techniques for these models’ evaluation, so the computational cost associated with the Markov models is softened by unconditionally stable methods, such as the Uniformization method. Besides, we search for solvers that keep a low memory consumption to enable the simulation of complex cardiac tissue.