ID Number		1550
Study Type		Engineering & Physics
Model		Computational Dosimetry Methods (catch all).
Details		Computational Dosimetry Methods (catch all) AUTHORS' ABSTRACT: Fahs et al. 2011 (IEEE #5177): The great majority of numerical calculations of the specific absorption rate (SAR) induced in human tissues exposed to microwaves are performed using the finite difference time-domain (FDTD) method and voxel-based geometrical models. The straightforward implementation of the method and its computational efficiency are among the main reasons for FDTD being currently the leading method for numerical assessment of human exposure to electromagnetic waves. However, the rather difficult departure from the commonly used Cartesian grid and cell size limitations regarding the discretization of very detailed structures of human tissues are often recognized as the main weaknesses of the method in this application context. In particular, interfaces between tissues where sharp gradients of the electromagnetic field may occur are hardly modeled rigorously in these studies. We present here an alternative numerical dosimetry methodology which is based on a high order discontinuous Galerkin time-domain (DGTD) method and adapted geometrical models constructed from unstructured triangulations of tissue interfaces, and discuss its application to the calculation of the SAR induced in head tissues. AUTHORS' ABSTRACT: Panagopoulos et al. 2013 (IEEE #5281): PURPOSE: To evaluate SAR as a dosimetric quantity for EMF bioeffects, and identify ways for increasing the precision in EMF dosimetry and bioactivity assessment. METHODS: We discuss the interaction of man-made electromagnetic waves with biological matter and calculate the energy transferred to a single free ion within a cell. We analyze the physics and biology of SAR and evaluate the methods of its estimation. We discuss the experimentally observed non-linearity between electromagnetic exposure and biological effect. RESULTS: WE FIND THAT: a) The energy absorbed by living matter during exposure to environmentally accounted EMFs is normally well below the thermal level. b) All existing methods for SAR estimation, especially those based upon tissue conductivity and internal electric field, have serious deficiencies. c) The only method to estimate SAR without large error is by measuring temperature increases within biological tissue, which normally are negligible for environmental EMF intensities, and thus cannot be measured. CONCLUSIONS: SAR actually refers to thermal effects, while the vast majority of the recorded biological effects from man-made non-ionizing environmental radiation are non-thermal. Even if SAR could be accurately estimated for a whole tissue, organ, or body, the biological/health effect is determined by tiny amounts of energy/power absorbed by specific biomolecules, which cannot be calculated. Moreover, it depends upon field parameters not taken into account in SAR calculation. Thus, SAR should not be used as the primary dosimetric quantity, but used only as a complementary measure, always reporting the estimating method and the corresponding error. Radiation/field intensity along with additional physical parameters (such as frequency, modulation etc) which can be directly and in any case more accurately measured on the surface of biological tissues, should constitute the primary measure for EMF exposures, in spite of similar uncertainty to predict the biological effect due to non-linearity. AUTHORS' ABSTRACT: Kurniawan, Wood and McIntosh 2015 (IEEE #5914): Analysis of near electric and magnetic field magnitudes and pattern in tissue layers due to exposure from a dipole antenna would normally require extensive electromagnetic computation, with significant computing resource and time. In this paper, the authors have developed an analytical approach to provide a fast, intuitive estimate of near field exposure by direct closed-form formulae, without the need of integration by numerical computation. A computational tool based on the proposed approach has been developed in MATLAB® to estimate near field exposure of various points of different tissue layers adjacent to a dipole operating in 900 MHz frequency. Results of this approach were obtained with significantly lower computational time when compared against those computed with a commercial Maxwell's equations solver FEKO®. Empirically-derived correction factors are introduced to adjust for the assumptions required in developing direct closed-form formulae. We found that the root mean square error in using the analytical formulae is less than 16.5% for considered scenarios, where we represent tissue layers with dielectric layers. The approach developed here is used to observe near fields at closer distance in comparison to previous literature, is capable to investigate fields at continuous resolution without requiring more computational resource, and has reconciled some discordant results in the literature. AUTHOR'S ABSTRACT" Dlugosz 2015 (IEEE #5932): The paper discusses several theoretical and practical aspects of the application of currents flowing through the body of a radiotelephone operator and Specific Absorption Rate (SAR). SAR is known as the physical quantity which is a perfect solution for biological experiments. Unfortunately, SAR cannot be measured directly. Contrary to SAR, which is limited to the penetration depth, a current induced in a point of a body is measurable in any other point of the body. The main objective of this paper is to show that the current induced in a human body when using a radiotelephone or mobile phone is significant and should be analyzed as widely as SAR is. Computer simulations of a humans hand with a radiotelephone were made. Experiments were also conducted. The results of the experiments show that induced current is also as important as SAR and it cannot be omitted in bioelectromagnetic experiments. In biomedical studies both parameters: induced current and SAR play a major role.
Findings
Status		Completed With Publication
Principal Investigator
Funding Agency		?????
Country		UNITED STATES
References		Hagmann, MJ et al. Microwave Power, (1987) 22:19-27 Moten, K et al. Bioelectromagnetics, (1989) 10:35-49 Moten, K et al. Bioelectromagnetics, (1991) 12:319-333 Kuster, N Appl. Computational Electromagnetics Soc. J., (1992) 7:43-60 Kuster, N et al. IEEE Trans. Vehicular Technol., (1992) 41:17-23 Gandhi, OP et al. Bioelectromagnetics., (1999) 20 (Supplement 4):93-101 Barber, PW IEEE Trans. Biomed. Eng., (1977) 24:513-521 Lin, JC IEEE Trans. Biomed. Eng., (1976) 23:371-375 Lin, JC IEEE Trans. Biomed. Eng., (1976) 23:61-65 Lin, JC et al. J. Microwave Power, (1976) 11:67-75 Gandhi, OP BIOLOGICAL EFFECTS AND MEDICAL APPLICATIONS OF ELECTROMAGNETIC ENERGY [BOOK], O.P. Gandhi (ed.), , (1990) :174-195 Chatterjee , I et al. Bioelectromagnetics., (1980) 1:379-388 Chatterjee , I et al. Bioelectromagnetics, (1980) 1:363-377 Sahalos, JN et al. Physiol Meas, (1994) 15 Suppl 2a:A65-A68 Silly-Carette, J et al. Ann Telecommun., (2008) 63:29-41 Balzano, Q et al. International Journal of Antennas and Propagation., (2007) 2007 (Article ID 57670):(8 pages)- Michishita , N et al. IEEE Transactions on Electromagnetic Compatibility. , (2012) 54:181-187 Fahs, H et al. 2010 URSI International Symposium on Electromagnetic Theory. , (2010) :547-550 Alouaz, O et al. Annals of Telecommunications. , (2011) 66:409-418 Panagopoulos , DJ et al. PLoS One., (2013) 8(6):- Tattersall, JE et al. Brain Res., (2001) 904:43-53 Dlugosz, T Bio-Medical Materials and Engineering., (2015) 225:1-7 Fahs, H et al. IEEE Trans. on Antennas and Propagation., (2011) 59:4669-4678 Vanderstraeten, J et al. Environ Res., (2020) 184:109387- Durney, CH et al. IEEE Trans Micro Theory Tech., (1979) 27:758-763 Xiong, J et al. IEEE Transactions on Vehicular Technology., (2021) doi.org/10.1109/TVT.2021.3085296:- Jiang, H et al. IEEE Commun Lett. , (2022) 26:1096-1100 Jiang, H et al. IEEE J. Sel. Topics Signal Process., (2022) 16:1055-1069
Comments