Abstract
This work presents an electro-mechanical model of the cardiac tissue and an automatic way to tune its parameters. A cellular automaton was used to simulate the action potential propagation, and a mass-spring system to model the tissue contraction. A parallel genetic algorithm was implemented in order to automatically adjust a simple and fast discrete model, to reproduce simulations of another synthetic well known model based on differential equations (DEs). Our results suggest that the discrete model was able to qualitatively reproduce the results obtained by DEs with much less computational effort.
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Acknowledgments
The authors thank CAPES, CNPq, FAPEMIG and UFJF for supporting this work.
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Campos, R.S., Rocha, B.M., da Silva Barra, L.P., Lobosco, M., dos Santos, R.W. (2015). A Parallel Genetic Algorithm to Adjust a Cardiac Model Based on Cellular Automaton and Mass-Spring Systems. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2015. Lecture Notes in Computer Science(), vol 9251. Springer, Cham. https://doi.org/10.1007/978-3-319-21909-7_15
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DOI: https://doi.org/10.1007/978-3-319-21909-7_15
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