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Specific absorption rates and induced current distributions in an anatomically based human model for plane-wave
1Department of Electrical Engineering, University of Utah, Salt Lake City 84112.
Health Physics
|September 1, 1992
Summary
This study used a high-resolution human body model to calculate specific absorption rates (SAR) from 100-915 MHz. Highest SAR for head and neck occurred at 150-200 MHz, with eye SAR increasing above 350 MHz.
Area of Science:
- Biophysics
- Computational Electromagnetics
- Medical Physics
Background:
- Previous studies reported specific absorption rates (SAR) and induced currents for lower frequencies (20-100 MHz) using a 5,628-cell human model.
- Advancements in computational power and modeling techniques enable higher resolution simulations.
Purpose of the Study:
- To extend SAR calculations to higher frequencies (up to 915 MHz) using a more detailed human body model.
- To investigate frequency-dependent SAR in various organs and body regions.
- To analyze the impact of grounding on SAR distribution.
Main Methods:
- Utilized a high-resolution, 45,024-cell anatomically based human body model.
- Employed the finite-difference time-domain (FDTD) method for electromagnetic wave absorption calculations.
- Calculated local, layer-averaged, and whole-body-averaged SAR for frequencies from 100-915 MHz.
Main Results:
- Highest part-body-averaged SAR for the head and neck region, including brain and eyes, observed at 200 MHz (isolated model) and 150 MHz (grounded model).
- Specific absorption rates for the eyes showed a consistent increase for frequencies above 350 MHz.
- Detailed SAR distributions were calculated for organs like the brain, eyes, heart, lungs, liver, kidneys, and intestines.
Conclusions:
- The high-resolution model provides detailed insights into human body exposure to radiofrequency electromagnetic fields.
- Frequency and grounding conditions significantly influence SAR distribution, particularly in the head and neck region.
- Findings are consistent with some existing experimental data and highlight the importance of high-resolution modeling for accurate SAR assessment.