Microwave Reflection-based Bladder State Discrimination with Realistic Pelvic Models: Impact of Urine Conductivity and Volume

Abstract

Microwave imaging could provide a low-cost, easy, and non-invasive method of detecting the state of the human bladder. However, current work on bladder detection uses relatively simple models. This paper presents a complex surface model of the human torso, based on the AustinMan model, to be used in broadband simulations. Model preparation is discussed, including the selection of dielectric properties of the tissues, bladder shape construction, and necessary simplifications to facilitate simulation of the model. Simulation results suggest that differences in the dielectric properties and volume of the urine are detectable through changes in the S11 parameter of the antenna.