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Signal Transmission with Intra-Body and Inter-Body Communications: Simulation-Based Models

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13th EAI International Conference on Body Area Networks (BODYNETS 2018)

Abstract

In this paper, we investigate two types of data transmission in human body communication (HBC) with galvanic coupling: Intra-body communication along a human arm and inter-body communication between two arms in touch. For the former, the effect of bending the arm is investigated, too. The arms were modeled as five-layers concentric cylinders of different types of tissues. For simulation, the finite element method (FEM) COMSOL Multiphysics5.3a software was used. The influence of different HBC key parameters including applied frequency, distance between transmitter (TX) and receiver (RX), bending, contact area between the contiguous models, and induced current was investigated. The results show that the transmission loss increases with the increase of the transmission length and operating frequency. The electrical potential is directly proportional to the induced current. Bending helps to improve the detected signal in the cases of short distance between TX and RX around the curvature. For distant transceivers, both straight and bended models tend to behave in a close manner. The signal degradation in inter-body communication is considerably higher compared to intra-body communication at the same horizontal distance between TX and RX. At frequencies above 200 kHz, both inter-body and intra-body communication give close values when the contact area between the arms covers the distance between TX and RX electrodes. In addition, by increasing the contact area and avoiding gaps between the models, the detected signal is improved. The results illustrate the main determinants of information transmission between both sensors within a body-sensors-network and between different persons.

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Correspondence to Doaa Ahmed .

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Ahmed, D., Kirchner, J., Fischer, G. (2020). Signal Transmission with Intra-Body and Inter-Body Communications: Simulation-Based Models. In: Sugimoto, C., Farhadi, H., Hämäläinen, M. (eds) 13th EAI International Conference on Body Area Networks . BODYNETS 2018. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-29897-5_14

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  • DOI: https://doi.org/10.1007/978-3-030-29897-5_14

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-29897-5

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