Genetic algorithms application for the optimal design of magnetic vagus nerve stimulator
Michał Chojnowski , Jacek Starzyński
Stimulation of human vagus nerve with use of electromagnetic field is intensively developing since late 1980's. The method pioneered by J. K. Penry and J. C. Dean is based on surgical implantation of electric device into human body and owes its prosperity to very promising results in various therapies. Its contemporary field of clinical applications stretches from epilepsy through depression and anxiety to migraines and still widens. Vagus nerve stimulation (VNS) was the initial trigger for authors to undertake the challenging research towards design of magnetic stimulator. Unlike the already well known electric VNS stimulator, the magnetic one (MVNS) is supposed to operate externally instead of being implanted into patient's body. The realistic, three-dimensional numerical model was prepared to begin with, in order to estimate the feasibility of the concept. One of the problems that emerged soon after the initial calculations were made, was to improve the basic design of the stimulator model. Having a complex, 3D model at hand to deal with a number of calculations required for an inverse problem meant a considerably long time of analysis and high demands for computational capacity. At that point, the need of model simplification became apparent and the most evident measure of bringing it into effect was to reduce the space of analysis into two dimensions. That assumption has conceived and brought to life a 2D model that proved to be less time and capacity consuming, compared to the three-dimensional one. This allowed use of the genetic algorithms for optimization of VNS applicator.
|Journal series||Progress in Electromagnetics Research Symposium, ISSN 1559-9450, (0 pkt)|
|Publication size in sheets||0.5|
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