A Combined Magnetoelectric Sensor and Human Head Model for Biomagnetic FEM Simulations

Abstract

We investigate a coupled multiscale 3D finite element model consisting of an orthogonal array of thin-film cantilever magnetoelectric magnetic field sensors and a simplified human head model. Electric point dipole sources are placed inside the head to generate an electromagnetic field. This field propagates through the tissue layers and outside of the head, where it reaches the sensor array. The investigated sensors are based on a 300 µm thick silicon substrate layer of 26.25 mm length and 2.45 mm width, with a 20 µm thick AlN layer and a 20 µm thick FeCoSiB layer as piezoelectric and magnetostrictive materials, respectively, located on opposite sides of the substrate. We position three sensors orthogonally to obtain a vector field sensor. The head model is based on the three-shell approach and consists of concentric spheres representing white matter, skull, and skin. All three layers are assigned specific conductivity and relative permittivity values from literature, aiming to approximate the propagation of electromagnetic fields through the different tissue types. We observe propagation of an electric field generated by the dipole source and subsequent induction of a magnetic field inside the head structure, propagating outwards to the sensor array, where the generated voltage in the piezoelectric layer is evaluated for different magnetoelectric sensor array and source positions and orientations. We show different behaviors of the sensors for a dipole source inside the head tissue versus a simple air environment, highlighting benefits in accuracy and specificity of a combined head and sensor model with realistic material parameters.

A Combined Magnetoelectric Sensor Array and MRI-Based Human Head Model for Biomagnetic FEM Simulation and Sensor Crosstalk Analysis

“…In order to create an approximation of the head and improve the previous spherical model [ 27 ], MRI-based medical images were processed into a 3D FEM model of the human head for this investigation. In the literature, there are now many open- and closed-source databases from which to extract these types of medical raw data.…”

“…We designed and implemented the ME sensor based on the ME sensor models from our previous work [ 26 , 27 ]. Each sensor consisted of a substrate layer of silicon with 26.25 mm length, 2.45 mm width, and 300 µm thickness, a magnetostrictive layer of FeCoSiB with 22.90 mm length, 1.80 mm width, and 20 µm thickness, and a piezoelectric layer of aluminum nitride (AlN) with 25.60 mm length, 1.60 mm width, and 20 µm thickness.…”

“…A linearized material model was used at the sensor’s small-signal working point. Details of the applied boundary conditions and physical properties of the three layers are described in our previous work [ 26 , 27 ].…”

“…This translated to a vastly different size and resolution of mesh elements for the differently sized domains, because the mesh is designed such that extremely thin layers are of a sufficiently small size, while larger domains are modeled with larges element sizes to reduce the computational load. The number of degrees of freedom (DOF) solved for in a combined model with three ME sensors demonstrated in previous work [ 27 ] is approximately 25 million, while the number increases to approximately 70 million DOF when including 15 ME sensors in the array. The number of DOF is determined by the amount of mesh elements, as well as the utilized physics in the model, and is an important figure of merit for the computational requirements to solve a given FEM model.…”

“…Using the mesh parameters given in Appendix B , we were not able to achieve a successful simulation run with a converged solution. In order to achieve a solution, we iteratively adjusted some parts of the mesh to be coarser than in the previous study [ 27 ], while keeping the mesh resolution as high as possible for the sensor geometry. The adjusted mesh parameters for this investigation step included the head geometry, the air environment, and the substrate layer of the ME sensors.…”