NDLI: A novel RF-based propagation model with tissue absorption for location of the GI tract

Content Provider	IEEE Xplore Digital Library
Author	Lujia Wang Li Liu Chao Hu Meng, M.Q.-H.
Copyright Year	2010
Description	Author affiliation: Department of Electronic Engineering, The Chinese University of Hong Kong, China (Meng, M.Q.-H.) \|\| Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China (Lujia Wang; Li Liu; Chao Hu)
Abstract	In order to accurately estimate (build) the radio signal propagation attenuation model, especially inside the gastro-intestine (GI) tract of the human body, the Radio Frequency (RF) absorption characterization in human body is investigated. This characterization provides a criterion to design the Received Signal Strength (RSS) based localization system for the objective inside the human body. In this paper, the Specific Absorption Rate (SAR), E-field, H-field of the near and far field are investigated at frequencies of 434MHz, 868MHz, 1.2GHz and 2.4GHz respectively. Then, the numerical electromagnetic analysis with the finite-differencetime-domain (FDTD) is applied to model the in vivo radio propagation channels by using a dipole antenna. Finally, simulation experiments are carried out in homogenous and heterogeneous mediums. The results show that the electromagnetic (EM) propagation is not only distance and orientation dependent, but also tissue absorption dependent in human body. The proposed model is in agreement with measurements in the simulation experiments.
Starting Page	654
Ending Page	657
File Size	461940
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627228
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological system modeling Mathematical model Equations Absorption Solid modeling Attenuation Numerical models
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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