Fast Model Order Reduction-Based Approach for Transcranial Magnetic Stimulation With Varying Coil Positioning

A nonlinear parametric model order reduction approach based on random selection of parameters and hyper-reduction is proposed and applied for the computation of the induced electric field in a subject’s head due to transcranial magnetic stimulation. The resulting reduced order model dramatically decreases computational times when simulating several positions and orientations of the excitation coil in a chosen region of interest. In particular the proposed model allows to obtain field solutions in a faster way with respect to classical solvers as Finite Element Methods without losing accuracy.