Techniques for Efficient Computation of Electric Fields Generated by Transcranial Direct-Current Stimulation
- Authors
- Lee, Chany; Kim, Euijin; Im, Chang-Hwan
- Issue Date
- May-2018
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Adaptive mesh refinement; domain decomposition method (DDM); error estimation; finite-element method (FEM); transcranial direct-current stimulation (tDCS)
- Citation
- IEEE TRANSACTIONS ON MAGNETICS, v.54, no.5, pp.1 - 5
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON MAGNETICS
- Volume
- 54
- Number
- 5
- Start Page
- 1
- End Page
- 5
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/16975
- DOI
- 10.1109/TMAG.2018.2794501
- ISSN
- 0018-9464
- Abstract
- Enhancement of computational efficiency is highly critical for finite-element analysis of electric fields generated by transcranial direct-current stimulation (tDCS) in order to foster field-analysis-based customized brain stimulation in practical scenarios. In this communication, we applied domain decomposition method (DDM) and adaptive mesh refinement method to the analysis of tDCS. DDM is likely to be particularly useful for tDCS field analysis problems with extracephalic reference electrodes. Our simulation results demonstrated that the DDM adopting the Schur complement method could reduce the overall computational time by 15% compared to the conventional single-domain analysis. On the other hand, to verify the enhancement of computational efficiency by adaptive mesh refinement, we used a realistic human head model with two sponge electrodes attached on the scalp surface. The distribution of numerical error estimated using an a posteriori error estimation method demonstrated that high errors were mostly concentrated on the edges and corners of the sponge electrodes. The overall solution accuracy could be remarkably enhanced by adding about 250 nodes around the high-error regions.
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