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A Fast Parallelized Computational Approach Based on Sparse LU Factorization for Predictions of Spatial and Time-Dependent Currents and Voltages in Full-Body Biomodels

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4 Author(s)
Mishra, A. ; Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA ; Joshi, R.P. ; Schoenbach, K.H. ; Clark, C.D.

Realistic and accurate numerical simulations of electrostimulation of tissues and full-body biomodels have been developed and implemented. Typically, whole-body systems are very complex and consist of a multitude of tissues, organs, and subcomponents with diverse properties. From an electrical standpoint, these can be characterized in terms of separate conductivities and permittivities. Accuracy demands good spatial resolution; thus, the overall tissue/animal models need to be discretized into a fine-grained mesh. This can lead to a large number of grid points (especially for a three-dimensional entity) and can place prohibitive requirements of memory storage and execution times on computing machines. Here, the authors include a simple yet fast and efficient numerical implementation. It is based on LU decomposition for execution on a cluster of computers running in parallel with distributed storage of the data in a sparse format. In this paper, the details of electrical tissue representation, the fast algorithm, the relevant biomodels, and specific applications to whole-animal studies of electrostimulation are discussed

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Plasma Science, IEEE Transactions on  (Volume:34 ,  Issue: 4 )