Multi-path Model and Sensitivity Analysis for Galvanic Coupled Intra-body Communication through Layered Tissue

TL;DR

This paper introduces a galvanic coupling-based intra-body communication model for implanted sensors, validated through simulations and experiments, offering a low-energy alternative to traditional RF methods for medical monitoring.

Contribution

It develops a comprehensive analytical model for galvanic intra-body communication in layered tissues, validated by simulations and experiments, enabling efficient channel characterization.

Findings

Model closely matches experimental data

Galvanic communication is energy-efficient

Parameter analysis informs device design

Abstract

New medical procedures promise continuous patient monitoring and drug delivery through implanted sensors and actuators. When over the air wireless radio frequency (OTA-RF) links are used for intra-body implant communication, the network incurs heavy energy costs owing to absorption within the human tissue. With this motivation, we explore an alternate form of intra-body communication that relies on weak electrical signals, instead of OTA-RF. To demonstrate the feasibility of this new paradigm for enabling communication between sensors and actuators embedded within the tissue, or placed on the surface of the skin, we develop a rigorous analytical model based on galvanic coupling of low energy signals. The main contributions in this paper are: (i) developing a suite of analytical expressions for modeling the resulting communication channel for weak electrical signals in a three dimensional multi-layered tissue structure, (ii) validating and verifying the model through extensive finite element simulations, published measurements in existing literature, and experiments conducted with porcine tissue, (iii) designing the communication framework with safety considerations, and analyzing the influence of different network and hardware parameters such as transmission frequency and electrode placements. Our results reveal a close agreement between theory, simulation, literature and experimental findings, pointing to the suitability of the model for quick and accurate channel characterization and parameter estimation for networked and implanted sensors.