Electromagnetic Modeling and Design of Medical Implants and Devices
This thesis covers two topics in biomedical electromagnetics: pacemaker lead heating in magnetic resonance imaging (MRI) and optimization of sensor
positions in magnetic tracking.
The electromagnetic part of pacemaker lead heating during MRI is a resonant phenomenon which is complicated by, among other factors, the wide range of length scales involved in the problem. In this work, the multi-scale
part of the problem is taken into special consideration during the modeling process. The model incorporates a radio frequency coil, a human body phantom,and a highly detailed model of a pacemaker system with a bipolar lead that features helix-shaped conductors.
Several configurations of pacemaker systems exposed to MRI are modeled and the results clearly show the importance of detailed lead modeling. Furthermore, modeling of resonant structures is investigated by a comparison between different modeling techniques. In addition, a meshing scheme
for thin-wire approximations of helices is proposed, evaluated, and found to have improved convergence properties as compared to the conventional meshing approach.
In recent years, magnetic tracking has been applied in many biomedical settings due to the transparency of the human body to low-frequency magnetic fields. In this work, the sensor positions of a magnetic tracking system are optimized by exploiting an analytical model where the transmitting and sensing coils of the system are approximated by magnetic dipoles.
In order to compare different sensor array layouts, two performance measures based on the Fisher information matrix are discussed and compared for the optimization of the sensor positions of a circular sensor array. Furthermore,
the sensor positioning problem is formulated as an optimization problem which is cast as a sensor selection problem. The sensor selection problem is solved for a planar sensor array by the application of a convex relaxation. Several transmitter positions are considered and general results are established for the dependence of the optimal sensor positions on the transmitter’s position and orientation.
Magnetic Resonance Imaging
Optimal Sensor Placement
Fisher Information Matrix
Room EC, EDIT building, Hörsalsvägen 11, Chalmers University of Technology
Opponent: Prof. Mats Gustafsson, Department of Electrical and Information Technology, Lund University, Lund, Sweden