# The Impact of Dual-Wavefront Propagation of Electromagnetic Waves in Bio-Tissues on Imaging and In-Body Communications

## TL;DR

This paper explores how electromagnetic waves split into two wavefronts in body tissues, affecting medical imaging and in-body communication accuracy.

## Contribution

The study introduces the concept of dual wavefronts in EM wave propagation through bio-tissues and their impact on medical applications.

## Key findings

- EM waves in bio-tissues split into phase and amplitude wavefronts at different angles.
- The Fermat principle is only accurate for low-loss tissues and matching media.
- Dual wavefronts must be considered for reliable medical imaging and communication.

## Abstract

Understanding how electromagnetic (EM) waves travel through different tissues is important for EM medical imaging, sensing, and in-body communication. It is known that EM waves in lossy bio-tissues are nonuniform and do not strictly follow the least time or least loss paths. Instead, they exhibit two distinct wavefronts: the phase wavefront and the amplitude wavefront, which are generally oriented at different angles. The impact of that on imaging and in-body communications is investigated and validated through comprehensive analysis and full-wave EM simulations. Additionally, the impact of a matching medium, commonly used to reduce antenna–skin interface reflections in medical EM applications, on the direction of EM wavefronts, travel time, phase changes, and attenuation is analyzed and quantified. The results show that the Fermat principle of least travel time, often used to estimate EM wave travel time for localization in medical imaging and wireless endoscopy, is only accurate when the loss tangent or dissipation factor of both the matching medium and tissues is very low. Otherwise, the results will be inaccurate, and the dual wavefronts should be considered. The presented analysis and results provide guidance on EM wave travel time and the direction of phase and amplitude wavefronts. This information is valuable for developing reliable processing algorithms for sensing, imaging, and in-body communication.