RESEARCH May 2026-Present
Analysis of Radiofrequency Propagation in Human Tissue
Biomedical Engineering · Computational Modeling with gprMax
My interest in how design and technology can solve real-world problems led me to explore how electromagnetic waves behave as they travel through the human body. Under the mentorship of Angela Pizzuto, Ph.D., Senior Research Engineer at RTX Technology Research Center, I’m using computational modeling to study radiofrequency propagation through different types of human tissue and its potential applications in biosensors and advanced prosthetics.
How do radiofrequency signals behave inside the human body?
This project investigates how electromagnetic waves propagate through different types of human tissue using computational modeling. By studying how radiofrequency signals change as they move through bone, muscle, and brain tissue, the goal is to better understand how this behavior could inform future medical technologies.
Starting with the Human Thigh
Using gprMax, I model how electromagnetic waves travel through different types of human tissue. I began by modeling a cross-section of the human thigh and comparing how signals behaved when the transmitter was placed in bone versus muscle.
From the Thigh to the Brain
Building on the thigh model, I applied the same computational approach to a more complex brain tissue model. By changing the transmitter’s location, I can compare how radiofrequency propagation patterns shift in different regions of the brain, without drawing conclusions beyond what the simulations show.
Learning Through the Process: Challenges & Discoveries
Much of this project has involved learning how to build, refine, and troubleshoot realistic simulations.
Determining Material Properties
One of the first challenges was determining the appropriate electromagnetic properties and dispersion parameters for each type of tissue. By utilizing different resources such as NICT databases, Springer Nature Link and through estimation, we overcame this challenge.
Troubleshooting and Validating the Models
Getting the simulations to run correctly required repeated troubleshooting. Errors in code or model parameters could produce inaccurate results or prevent a simulation from running. Rather than treating each error as a setback, I learned to systematically check the code, isolate variables, and compare results against expected physical behavior. This helped me develop a more careful approach to computational research.
Discovering How Geometry Changes Propagation
As I moved from the thigh model to the more complex brain model, I began to see how the structure and arrangement of different tissues influence propagation patterns. Changing the transmitter's location also produced differences in how the simulated waves traveled through the surrounding tissue.
Where Could This Lead?
What excites me most is seeing how a computational model can connect to real-world problems. Understanding how electromagnetic waves interact with human tissue could contribute to future biosensors, medical devices, smart implants, and prosthetics. These are potential applications, not outcomes demonstrated by this research, but they help frame why this work matters.
MENTORSHIP
Angela Pizzuto, Ph.D.
Senior Research Engineer at RTX Technology Research Center
New Hartford, Connecticut
Research in Practice
Cross section of a leg at 2380 MHz.
- Embedded transmitter in bone
- Receiver outside leg
No leg at 2380 MHz for comparison.
- Transmitter and receiver are in the same places
- Signal reaches the receiver faster when there are no obstacles; less energy (amplitude) and time
Cross section of a brain at 500 MHz.
- Embedded transmitter in white matter
- Receiver outside brain
Cross section of a brain at 500 MHz.
- Embedded transmitter between grey matter and the skull
- Receiver outside brain, the same length away as the white matter
- Signal reaches receiver faster; less obstacles