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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoyi Min Kent, A.R. Rosenberg, S.P. Fayram, T.A. |
| Copyright Year | 2014 |
| Description | Author affiliation: St. Jude Med., Sunnyvale, CA, USA (Kent, A.R.; Fayram, T.A.) || St. Jude Med., Sylmar, CA, USA (Xiaoyi Min; Rosenberg, S.P.) |
| Abstract | A recently published computational modeling study of spinal cord stimulation (SCS) predicted that a multiple current source (MCS) system could generate a greater number of central points of stimulation in the dorsal column (DC) than a single current source (1CS) system. However, the clinical relevance of this finding has not been established. The objective of this work was to compare the dermatomal zone selectivity of MCS and 1CS systems. A finite element method (FEM) model was built with a representation of the spinal cord anatomy and a 2×8 paddle electrode array. Using a contact configuration with two aligned tripoles, the FEM model was used to solve for DC field potentials across incremental changes in current between the two cathodes, modeling the MCS and 1CS systems. The activation regions within the DC were determined by coupling the FEM output to a biophysical nerve fiber model, and coverage was mapped to dermatomal zones. Results showed marginal differences in activated dermatomal zones between 1CS and MCS systems. This indicates that a MCS system may not provide incremental therapeutic benefit as suggested in prior analysis. |
| Sponsorship | IEEE Eng. Med. Biol. Soc. |
| Starting Page | 6246 |
| Ending Page | 6249 |
| File Size | 856042 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424479290 |
| ISSN | 1557170X |
| DOI | 10.1109/EMBC.2014.6945056 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-26 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cathodes Computational modeling Nerve fibers Biological system modeling Finite element analysis Electrical stimulation Solid modeling |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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