Computational Electromagnetics Enables Personalized Medicine: A Case Study in Transcranial Magnetic Stimulation
As we enter the era of personalized medicine, electromagnetic and wireless performance has become increasingly important to the control and functionality of implantable devices, imaging modalities, and non-invasive stimulation techniques. I describe a framework for coil design and uncertainty quantification for next-generation transcranial magnetic stimulation (TMS), a noninvasive brain stimulation technique used for research and clinical applications. The framework designs coils that double the precision of spatial targeting (focality) of existing TMS coils. This is the first significant advancement in the depth-focality trade-off of TMS coils since the introduction of the standard figure-of-eight coil three decades ago, and likely represents the fundamental physical limit. Moreover, the framework quantifies uncertainty in TMS induced electric fields due to system setup and patient variability, and it identifies key parameters that affect targeting. Results show that coil position is a key contributor to TMS variability, supporting the need for more precise neuro-navigation devices. Finally, I will present a novel general-purpose electromagnetics solver that can be used for a wide range of applications like TMS, MRI imaging modalities, negative permittivity plasmas, and near-zero/low permittivity metamaterials. This solver uses a novel integral equation formulation that, unlike other solvers, does not exhibit high/negative permittivity and low-frequency breakdowns.