Literature DB >> 25014932

Investigation of galvanic-coupled intrabody communication using the human body circuit model.

Behailu Kibret, MirHojjat Seyedi, Daniel T H Lai, Micheal Faulkner.   

Abstract

Intrabody Communication (IBC) is a technique that uses the human body as a transmission medium for electrical signals to connect wearable electronic sensors and devices. Understanding the human body as the transmission medium in IBC paves way for practical implementation of IBC in body sensor networks. In this study, we propose a model for galvanic coupling-type IBC based on a simplified equivalent circuit representation of the human upper arm. We propose a new way to calculate the electrode-skin contact impedance. Based on the model and human experimental results, we discuss important characteristics of galvanic coupling-type IBC, namely, the effect of tissues, anthropometry of subjects, and electrode configuration on signal propagation. We found that the dielectric properties of the muscle primarily characterize the received signal when receiver electrodes are located close to transmitter electrodes. When receiver and transmitter electrodes are far apart, the skin dielectric property affects the received signal.

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Year:  2014        PMID: 25014932     DOI: 10.1109/JBHI.2014.2301165

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  10 in total

1.  Electrical Impedance as a Noninvasive Metric of Quality in Allografts Undergoing Normothermic Ex Vivo Lung Perfusion.

Authors:  Danielle M Peterson; Eliza W Beal; Brenda F Reader; Curtis Dumond; Sylvester M Black; Bryan A Whitson
Journal:  ASAIO J       Date:  2022-01-20       Impact factor: 3.826

2.  Evaluation and Verification of Channel Transmission Characteristics of Human Body for Optimizing Data Transmission Rate in Electrostatic-Coupling Intra Body Communication System: A Comparative Analysis.

Authors:  Yuhwai Tseng; Chauchin Su; Yingchieh Ho
Journal:  PLoS One       Date:  2016-02-11       Impact factor: 3.240

3.  Evaluation of Propagation Characteristics Using the Human Body as an Antenna.

Authors:  Jingzhen Li; Zedong Nie; Yuhang Liu; Lei Wang; Yang Hao
Journal:  Sensors (Basel)       Date:  2017-12-11       Impact factor: 3.576

4.  The Modeling and Simulation of the Galvanic Coupling Intra-Body Communication via Handshake Channel.

Authors:  Maoyuan Li; Yong Song; Wansong Li; Guangfa Wang; Tianpeng Bu; Yufei Zhao; Qun Hao
Journal:  Sensors (Basel)       Date:  2017-04-14       Impact factor: 3.576

Review 5.  Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges.

Authors:  Ivana Čuljak; Željka Lučev Vasić; Hrvoje Mihaldinec; Hrvoje Džapo
Journal:  Sensors (Basel)       Date:  2020-06-25       Impact factor: 3.576

6.  Characterization of the Fat Channel for Intra-Body Communication at R-Band Frequencies.

Authors:  Noor Badariah Asan; Emadeldeen Hassan; Jacob Velander Syaiful Redzwan Mohd Shah; Daniel Noreland; Taco J Blokhuis; Eddie Wadbro; Martin Berggren; Thiemo Voigt; Robin Augustine
Journal:  Sensors (Basel)       Date:  2018-08-21       Impact factor: 3.576

7.  A Variable-Volume Heart Model for Galvanic Coupling-Based Conductive Intracardiac Communication.

Authors:  Yiming Liu; Yueming Gao; Liting Chen; Tao Liu; Jiejie Yang; Siohang Pun; Mangi Vai; Min Du
Journal:  Sensors (Basel)       Date:  2022-06-12       Impact factor: 3.847

8.  A Novel Field-Circuit FEM Modeling and Channel Gain Estimation for Galvanic Coupling Real IBC Measurements.

Authors:  Yue-Ming Gao; Zhu-Mei Wu; Sio-Hang Pun; Peng-Un Mak; Mang-I Vai; Min Du
Journal:  Sensors (Basel)       Date:  2016-04-02       Impact factor: 3.576

9.  Electrical exposure analysis of galvanic-coupled intra-body communication based on the empirical arm models.

Authors:  Yue-Ming Gao; Heng-Fei Zhang; Shi Lin; Rui-Xin Jiang; Zhi-Ying Chen; Željka Lučev Vasić; Mang-I Vai; Min Du; Mario Cifrek; Sio-Hang Pun
Journal:  Biomed Eng Online       Date:  2018-06-05       Impact factor: 2.819

10.  Biometric Identity Based on Intra-Body Communication Channel Characteristics and Machine Learning.

Authors:  Ahmed E Khorshid; Ibrahim N Alquaydheb; Fadi Kurdahi; Roger Piqueras Jover; Ahmed Eltawil
Journal:  Sensors (Basel)       Date:  2020-03-05       Impact factor: 3.576

  10 in total

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