AUTHOR=Roopnarine Aaron , Rocke Sean 

TITLE=Multiphysics finite element investigation of galvanic transmission in dynamic human body communications

JOURNAL=Frontiers in Antennas and Propagation

VOLUME=Volume 3 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/antennas-and-propagation/articles/10.3389/fanpr.2025.1509439

DOI=10.3389/fanpr.2025.1509439

ISSN=2813-4680

ABSTRACT=IntroductionHuman body communication (HBC) utilizes the human body as a medium of communicating data. Considerable research has been done to characterize HBC channels to optimize communication techniques. However, dynamic HBC channels have been less studied.MethodsAn approach for developing dynamic models of the human body channel for galvanic communication is presented using multiphysics finite element analysis (FEA). An analytical framework is formulated that utilizes stochastic ABCD network parameters to explore and model dynamic HBC channel segments. Channel segments were subjected to mechanical forces using the finite element method (FEM) to reveal their impact on the current density and electric field.ResultsLinear regression modeling shows a strong relationship between applied force, current frequency, and channel response, with R² metrics exceeding 0.99. The dynamic nature of the channel reflects the need for stochastic modeling. This study examined candidate probability density functions (PDFs) to describe channel fading for the ABCD network parameters. Lognormal and Weibull distributions fit the magnitudes best while the generalized Pareto, generalized extreme value, and logistic distributions fit the phases best. Empirical modeling validated the accuracy of the lognormal distribution fits found using the FEM.DiscussionThe dynamic channel was characterized utilizing multiphysics FEM modeling, empirical modeling, and ABCD network parameters. This information is invaluable for EM dosimetry analysis and risk assessment in body area network (BAN) device design, as well as device optimization, because stochastic HBC parameters emulate the dynamic nature of the human body channel.