POD-DEIM reduction of computational EMG models
| Autor: | Daniel Wirtz, Thomas Heidlauf, Timm Strecker, Oliver Röhrle, Mylena Mordhorst |
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| Rok vydání: | 2017 |
| Předmět: |
Model order reduction
Mathematical optimization Speedup General Computer Science 0206 medical engineering Degrees of freedom (statistics) 010103 numerical & computational mathematics 02 engineering and technology 020601 biomedical engineering 01 natural sciences Projection (linear algebra) Theoretical Computer Science Reduction (complexity) Nonlinear system Modeling and Simulation 0101 mathematics Galerkin method Algorithm Mathematics Interpolation |
| Zdroj: | Journal of Computational Science. 19:86-96 |
| ISSN: | 1877-7503 |
| DOI: | 10.1016/j.jocs.2017.01.009 |
| Popis: | This article presents an application of model order reduction techniques to a numerical model computing electromyographic (EMG) signals. The considered EMG model is a combination of the extracellular bidomain equation with a parameterized nonlinear membrane voltage source. Key ingredients for the proposed reduction methodology are Galerkin projection via proper orthogonal decomposition and application of the discrete empirical interpolation method to the nonlinear source term. The computational efficiency of the approach is demonstrated by numerical examples comparing the reduced model to the full (non-reduced) model. In detail, a high-fidelity model of ≈100 000 degrees of freedom is successfully reduced by several orders of magnitude whilst preserving accuracy and gaining a computational speedup of up to 180. Thus, using the proposed method a realistic number of muscle fibres and motor units can be considered in numerical EMG simulations, which is not feasible using full models due to their high computational cost. |
| Databáze: | OpenAIRE |
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