Faculty Advisor or Committee Member

Yishuang Geng, Committee Member

Faculty Advisor or Committee Member

Kaveh Pahlavan, Advisor

Faculty Advisor or Committee Member

Sergey N. Makarov, Committee Member

Faculty Advisor or Committee Member

John A. McNeill, Department Head




Localization inside the human body using radio frequency (RF) transmission is gaining importance in a number of applications such as Wireless Video Capsule Endoscopy. The accuracy of RF localization depends on the technology adopted for this purpose. The two most common RF localization technologies use received signal strength (RSS) and time-of-arrival (TOA). This research presents a comparison of the accuracy of TOA and RSS based localization inside human tissue using computational techniques for simulation of radio propagation inside human tissues. Computer simulation of the propagation of radio waves inside the human body is extremely challenging and computationally intensive. We designed a basic, MATLAB coded, finite difference time-domain (FDTD) for the radio propagation in and around the human body and compared the results obtained from this software with the commonly used and commercially available Finite Element Method (FEM) modeling in ANSYS HFSS. We first show that the FDTD analysis yields comparable results. Then we use the software to simulate the RSS and TOA of the wideband signals propagated inside the human body for RF localization to compare the accuracies of the two methods. We then develop a statistical TOA model using empirical data gathered from these simulations; and, in conjunction with pre-established mathematical models for RSS, we compare the accuracy of each technique with the Cramer-Rao Lower Bound (CRLB) commonly used for calculation of bounds for the performance of localization techniques and the effects of human body movements.


Worcester Polytechnic Institute

Degree Name



Electrical & Computer Engineering

Project Type


Date Accepted





wireless health, Radio propagation, Localization, Body area networks