<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Human body communication (HBC) uses the human body as the channel to transfer data. Extensive work has been done to characterize the human body channel for different HBC techniques and scenarios. However, statistical channel bioimpedance characterisation of human body channels, particularly under dynamic conditions, remains relatively understudied. This paper develops a stochastic fading bioimpedance model for the human body channel using Monte Carlo simulations. Differential body segments were modelled as 2-port networks using ABCD parameters which are functions of bioimpedance based body parameters modelled as random variables. The channel was then modelled as the cascade of these random 2-port networks for different combinations of probability distribution functions (PDFs) assumed for the bioimpedance-based body parameters. The resultant distribution of the cascaded body segments varied for the different assumed bioimpedance based body parameter distributions and differential body segment sizes. However, considering the distribution names that demonstrated a best fit (in the top 3 PDF rankings) with highest frequency under the varying conditions, this paper recommends the distribution names: Generalized Pareto for phase distributions and Log-normal for magnitude distributions for each element in the overall cascaded random variable ABCD matrix.</p></abstract>

Human body communication (HBC) uses the human body as the channel to transfer data. Extensive work has been done to characterize the human body channel for different HBC techniques and scenarios. However, statistical channel bioimpedance characterisation of human body channels, particularly under dynamic conditions, remains relatively understudied. This paper develops a stochastic fading bioimpedance model for the human body channel using Monte Carlo simulations. Differential body segments were modelled as 2-port networks using ABCD parameters which are functions of bioimpedance based body parameters modelled as random variables. The channel was then modelled as the cascade of these random 2-port networks for different combinations of probability distribution functions (PDFs) assumed for the bioimpedance-based body parameters. The resultant distribution of the cascaded body segments varied for the different assumed bioimpedance based body parameter distributions and differential body segment sizes. However, considering the distribution names that demonstrated a best fit (in the top 3 PDF rankings) with highest frequency under the varying conditions, this paper recommends the distribution names: Generalized Pareto for phase distributions and Log-normal for magnitude distributions for each element in the overall cascaded random variable ABCD matrix.

Stochastic Bioimpedance-Based Channel Model of the Human Body for Galvanic Coupling

Journal of Electrical Bioimpedance

This work is licensed under the Creative Commons Attribution 4.0 International License.

Human body communication (HBC) uses the human body as the channel to transfer data. Extensive work has been done to characterize the human body channel for...

Stochastic Bioimpedance-Based Channel Model of the Human Body for Galvanic Coupling

Pubblicato online: 27 dic 2021

Pagine: 117 - 124

Ricevuto: 03 giu 2021

DOI: https://doi.org/10.2478/joeb-2021-0014

Parole chiave
Human body communications (HBC), bioimpedance, organic communication channels (OCC), propagation modelling

© 2021 Aaron Roopnarine and Sean A. Rocke, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Stochastic Bioimpedance-Based Channel Model of the Human Body for Galvanic Coupling

Pubblicato online: 27 dic 2021

Pagine: 117 - 124

Ricevuto: 03 giu 2021

DOI: https://doi.org/10.2478/joeb-2021-0014

Parole chiaveHuman body communications (HBC), bioimpedance, organic communication channels (OCC), propagation modelling

© 2021 Aaron Roopnarine and Sean A. Rocke, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Human body communications (HBC), bioimpedance, organic communication channels (OCC), propagation modelling