Document Type
Article
Publication Date
2006
DOI
10.1109/tps.2006.876485
Publication Title
IEEE Transactions on Plasma Science
Volume
34
Issue
4
Pages
1431-1440
Abstract
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.
Original Publication Citation
Mishra, A., Joshi, R. P., Schoenbach, K. H., & Clark, C. D. (2006). A fast parallelized computational approach based on sparse LU factorization for predictions of spatial and time-dependent currents and voltages in full-body biomodels. IEEE Transactions on Plasma Science, 34(4), 1431-1440. doi:10.1109/tps.2006.876485
Repository Citation
Mishra, Ashutosh; Joshi, Ravindra P.; Schoenbach, Karl H.; and Clark, C. D. III, "A Fast Parallelized Computational Approach Based on Sparse LU Factorization for Predictions of Spatial and Time-Dependent Currents and Voltages in Full-Body Biomodels" (2006). Electrical & Computer Engineering Faculty Publications. 158.
https://digitalcommons.odu.edu/ece_fac_pubs/158
Comments
Web of Science: "Free full-text from publisher -- gold open access."