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Erschienen in: Medical & Biological Engineering & Computing 6/2019

23.02.2019 | Original Article

Combination of “quadratic adaptive algorithm” and “hybrid operator splitting” or uniformization algorithms for stability against acceleration in the Markov model of sodium ion channels in the ventricular cell model

verfasst von: Xing-Ji Chen, Ching-Hsing Luo, Min-Hung Chen, Xiang Zhou

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 6/2019

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Abstract

The Markovian model has generally been used for cardiac electrophysiological simulations. However, the Markovian model is so stiff that speeding up the computation of the algorithms with variable time-steps always results in simulation instability. In particular, the unstable simulations always occur at a low voltage rate or current change, while transition rates in the Markovian model are changing markedly. The uniformization (UNI) method allows for a Markovian model simulation with high stability but also a high computation cost. To save computation costs with variable time-steps, we propose a speed increasing idea that is a compromise to the trade-off between stability and acceleration by combining Chen-Chen-Luo’s “quadratic adaptive algorithm” (CCL) method with “hybrid operator splitting” (HOS) into the solver (CCL + HOS solver). The computation cost of this CCL + HOS solver is approximately 24 times lower than the CCL + UNI solver, and the CCL + HOS solver can function 295 times faster in comparison to the HOS solver with a fixed time-step (DT). The suggested optimal solver should be CCL + HOS solver with a maximum time-step at 0.1 ms due to its high speed with low error. Additionally, the CCL method has much better performance and stability than the hybrid method in this single-cell model simulation.

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Metadaten
Titel
Combination of “quadratic adaptive algorithm” and “hybrid operator splitting” or uniformization algorithms for stability against acceleration in the Markov model of sodium ion channels in the ventricular cell model
verfasst von
Xing-Ji Chen
Ching-Hsing Luo
Min-Hung Chen
Xiang Zhou
Publikationsdatum
23.02.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 6/2019
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-019-01956-5

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