Modeling of the electromagnetic, structural, thermal, or acoustic response of the human body to various external and internal stimuli is limited by the availability of anatomically accurate and numerically efficient computational models. The models currently approved for use are generally of proprietary or fixed format, preventing new model construction or customization. 1. This dissertation develops a new Visible Human Project - Female (VHP-F) computational phantom, constructed via segmentation of anatomical cryosection images taken in the axial plane of the human body. Its unique property is superior resolution on human head. In its current form, the VHP-F model contains 33 separate objects describing a variety of human tissues within the head and torso. Each obejct is a non-intersecting 2-manifold model composed of contiguous surface triangular elements making the VHP-F model compatible with major commercial and academic numerical simulators employing the Finite Element Method (FEM), Boundary Element Method (BEM), Finite Volume Method (FVM), and Finite-Difference Time-Domain (FDTD) Method. 2. This dissertation develops a new workflow used to construct the VHP-F model that may be utilized to build accessible custom models from any medical image data source. The workflow is customizable and flexible, enabling the creation of standard and parametrically varying models facilitating research on impacts associated with fluctuation of body characteristics (for example, skin thickness) and dynamic processes such as fluid pulsation. 3. This dissertation identifies, enables, and quantifies three new specific computational bioelectromagnetic problems, each of which is solved with the help of the developed VHP-F model: I. Transcranial Direct Current Stimulation (tDCS) of human brain motor cortex with extracephalic versus cephalic electrodes; II. RF channel characterization within cerebral cortex with novel small on-body directional antennas; III. Body Area Network (BAN) characterization and RF localization within the human body using the FDTD method and small antenna models with coincident phase centers. Each of those problems has been (or will be) the subject of a separate dedicated MS thesis.

About fifty years ago, research began in the field of computational human phantoms primarily for radiation dose calculations. This field has grown exponentially due to the potential for solving complicated medical problems. Modeling electromagnetic, structural, thermal, and acoustic response of the human body to different internal and external stimuli has been limited by the availability of numerically efficient computational human models. This study describes the recent development of a computational full-body human phantom €“ Visible Human Project (VHP) €“ Female Model. This human phantom has been validated for certain frequencies in the ISM band and beyond. The anatomical accuracy of the phantom is established by comparing the CAD phantom with the original VHP image dataset. This thesis also applies the VHP €“ Female CAD Model (version 3.1) for investigating the effects of MRI radiation. The simulation environment ANSYS HFSS is used for studying the effects of RF birdcage coil on the human phantom. Finally, a non-ionizing technique for osteoporosis detection is investigated numerically.

This study presents mathematical surrogate models, derived from finite element kinematic response data, to predict car crash-induced occupant head and neck injury risk for a broad range of impact velocities (10 – 45 mph), impact locations, and angles of impact (-45° to 45°). The development of these models allowed for wide-scale injury prediction while significantly reducing the overall required number of impact test cases. From these, increases in both the impact velocity and the impact’s locational proximity to the occupant were determined to result in the greatest head and neck injury risks. Additionally, strong interactions between the impact orientation variables (location and angle) produced significant changes in the head injury risk, while the neck injury risk was relatively insensitive to these interactions; likely due to the uniaxiality of the current standard neck injury risk metrics. Overall, this methodology showed potential for future applications in wide-scale injury prediction or vehicular design optimization.