DOSIMETRY FOR EVALUATING EM FIELDS WITHIN HUMAN BODY

Riadh W. Y. Habash¹ and Hafid T. Alhafid²
¹ School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada
² School of Information Technology, Dubai University College, UAE

Abstract: This paper outlines recent studies of bioelectromagnetic problems, including the application of theoretical and experimental methods to calculate the internal fields and currents induced in biological systems exposed to extremely low frequency (ELF) fields and radio frequency radiation (RFR).

INTRODUCTION

The aim of dosimetry is to estimate the electric fields, induced currents, or specific absorption rate (SAR) distributions in objects like models, animals, or humans exposed to EM fields. Data from such studies is essential for the development of dependable standards.

Numerical dosimetry is employed as a major tool in various biological geometries and structures. However, experimental dosimetry provides a viable means for estimating the absorbed fields under environments that exceed the capabilities of the existing computational techniques [1].

In this paper, we just present few recent research investigations for the estimation of electric fields, induced currents, and warmth sensation in head and body models due to exposure from various EM sources. This overview may help in addressing the problem of EM interaction with human body for an age in which technology is advancing and the impact of that technology may not be known for years.

DOSIMETRIC STUDIES

There have been several dosimetric research papers published in peer-reviewed journals that estimates absorbed fields associated with exposure to ELF fields as well as RFR.

A practical example of the electric fields and current densities induced in a human body in close proximity to a 60-Hz transmission line was evaluated by Potter et al. [2]. The total-scattered field formulation was employed, along with a quasi-static formulation of the finite-difference time-domain (FDTD) method. The results for predicted organ dosimetry are compared with predictions for the uniform electric field. The demonstrated induced fields and current densities were significantly higher than originally predicted for the uniform electric field exposure on a ground plane.

Contact currents in models of an adult and a child have been computed numerically by Dawson et al. [3]. They found that the electric fields in the child model are higher than in the adult model by a factor of two to three. A lack of consistency was seen between the contact current reference levels and the basic restrictions in the exposure guidelines [4].

Gandhi [5] used both numerical and experimental techniques to estimate SARs in human head for ten cellular phones from four different manufacturers. The computation results were verified using a head-shaped model. The results were summarized as follows: peak SAR over any 1 g of tissue 0.09-0.29 W/kg; peak SAR over any 1 g of brain tissue 0.04-0.17 W/kg; and whole body SAR 0.5-1.1 mW/kg.

These figures differ with those obtained by Dimbylow [6] who used FDTD method on 5´105 cells in 2 mm³ voxels in a MRI acquired image of a human head. He showed SAR values 3.1 W/kg averaged over 10 gm tissues inside the head. SAR averaged over 1 gm of tissue was 4.7 W/kg for a l/4 monopole antenna at 900 MHz. At 1.8 GHz the maximum SAR values along the side of the head were 4.6 and 7.7 W/kg for 10 and 1 gm of tissue, respectively. The maximum emitted power required to meet the ANSI/IEEE guidelines for public environments (1.6 W/kg) is 0.34 W at 900 MHz.

Balzano et al. [7] measured SAR induced in human-equivalent phantoms by two types of Motorola cellular phones. They found SAR as high as 1.4 W/kg for “Flip” phones.

Kuster [8] measured 16 different European digital phones under normal user conditions. He could observe wide variation in the SAR values. The phone with lowest SAR, when averaged over 10 g tissue, had a SAR of 0.28 W/kg, while the highest had 1.33 W/kg, all normalized to an input power of 0.25 W. The value may go from 0.2 to 3.5 W/kg if the phone is slightly tilted. Accordingly, the way the phone is placed widely affects SAR values.

Chen et al. [9] combined the FDTD with the method of moments (MoM) to analyze SAR and the magnetic field in a realistic human head model excited by shielded RF coils for high frequency magnetic resonance imaging (MRI) applications at 64, 128, 171, and 256 MHz. The results show that the value of SAR increases when the frequency of the magnetic field increases. Also, the magnetic field exhibited a strong inhomogeneity at high frequencies.

Gandhi et al. [10] employed the FDTD method to calculate SARs and radiation patterns of few handheld phones. Automated SAR and radiation pattern measurement systems were used to validate both the calculated 1-g SARs and radiation patterns for several telephones. Even though widely different peak 1-g SARs were obtained, ranging from 0.13 to 5.41 W/kg, agreement between the calculated and the measured data for these phones, five each at 835 and 1900 MHz, was excellent. For a maximum radiated power of 600 mW at 800/900 MHz, the peak 1-g SAR could be higher than 1.6 W/kg.

Van Leeuwen et al. [11] evaluated the 3D-temperature rise induced by a mobile phone inside a realistic head model using an FDTD model. The researchers calculated a maximum rise in brain temperature of 0.11^oC for antenna with an average emitted power of 0.25 W. Maximum temperature rise was at the skin. A maximum averaged SAR characterized the power distributions over an arbitrarily shaped 10-g volume of approximately 1.6 W/kg.

Wainwright [12] developed a finite element thermal model of the head to calculate temperature rises in the brain by radiation from cellular phones and similar devices. The temperature distribution was calculated using the standard bioheat equation. It was observed that in the normal cerebral cortex the high blood perfusion rate serves to provide an efficient cooling mechanism. The maximum temperature rise found in the brain was about 0.1°C.

REFERENCES

[1] Habash, R. W. Y., Electromagnetic Fields and Radiation: Human Bioeffects and Safety, Marcel Dekker, New York, NY, 2001.

[2] Potter, M. E., M. Okoniewski, and M. A. Stuchly, Low Frequency Finite Difference Time Domain (FDTD) for Modeling of Induced Fields in Humans Close to Line Sources, Journal of Computational Physics 162, pp. 82-103, 2000.

[3] Dawson T. W., K. Caputa, M. A. Stuchly, and R. Kavet, Induced Electric Fields in the Human Body Associated with 60 Hz Contact Currents, IEEE Transactions on Biomedical Engineering 48, pp. 1020-1026, 2001.

[4] International Commission on Non-Ionizing Radiation Protection (ICNIRP), Guidelines for Limiting Exposure to Time-Varying Electric Magnetic and Electromagnetic Fields (up to 300 GHz, Health Physics 74, pp. 494-522, 1998.

[5] Gandhi, O. P., ANSI Radiofrequency Safety Guide: Its Rationale, Some Problems and Suggested Improvements, In Biological Effects and Medical Applications of Electromagnetic Energy (ed. Gandhi, O. P.), pp. 29-46, Prentice Hall, Engelwood, NJ, 1990.

[6] Dimbylow, P. J., FDTD Calculations at the SAR for a Dipole Closely Coupled to the Head at 900 MHz and 1.9 GHz, Physics in Medicine and Biology 38, pp. 361-368, 1993.

[7] Balzano, Q., O. Garay, and T. J. Manning, Electromagnetic Energy Exposure of Simulated Users of Portable Cellular Telephones, IEEE Trans. on Vehicular Tech. 44, pp. 390-403, 1995.

[8] Kuster, N., Swiss Tests Show Wide Variation in Radiation Exposure from Cell Phones, Microwave News, pp. 10-11, 1997.

[9] Chen, Ji, Z. Feng, J. –M. Jin, Numerical Simulation of SAR and B₁-field Inhomogeneity of Shielded RF Coils Loaded with the Human Head, IEEE Transactions on Biomedical Engineering 45, pp. 650-655, 1998.

[10] Gandhi, O. P., L. Gianluca, A. Tinniswood, and Q. -S. Yu, Comparison of Numerical and Experimental Methods for Determination of SAR and Radiation Patterns of Handheld Wireless Telephones, Bioelectromagnetics 20, pp. 93-101, 1999.

[11] Van Leeuwen, G. M., J. J. Lagendijk, B. J. Van Leersum, A. P. Zwamborn, S. N. Hornsleth, and A. N. Kotte, Calculation of Change in Brain Temperatures Due to Exposure to a Mobile Phone, Physics in Medicine and Biology 44, pp. 2367-2379, 1999.

[12] Wainwright, P., Thermal Effects of Radiation from Cellular Telephones, Physics in Medicine and Biology 45, pp. 2363-2372, 2000.