Comparison of artifact elimination strategies during postprocessing for the numerical assessment of localized low frequency magnetic field exposure of the hand

Abstract Numerical computations of induced electric field strength E i inside the human body are prone to so-called “staircasing errors”, i.e., physically incorrect local enhancements of the computed E i ate such numerical artifacts, ICNIRP suggested in their 2010 guidelines to use the 99 th percentile of the distribution of the 2 x 2 x 2 mm 3 at the edges of the cubical cells. Similar artifacts can occur due to imperfections in the anatomical body models used. In order to elimin averaged induced electric field strength Ei,avg for comparison with the basic restrictions instead of the maximum computed E i,avg value. However, this suggestion was based on very early computational studies using anatomical body models with relatively low spatial resolution. Moreover, a 99 th percentile-based assessment of E i,avg appears generally questionable in case of highly localized exposure scenarios, where large fractions of the body remain almost unexposed, and therefore true local hot spots of Ei,avg that should be considered may be excluded from the analysis, simply because the exposed tissue fraction is less than 1 % of the total body volume. Although this problem has been repeatedly pointed out by several research groups in the past, the 99 th percentile-based assessment unfortunately spread out as a “general rule” into some guidelines for exposure assessment. Consequently, the compliance of many devices on the market with exposure limits can be questioned. In this paper we are quantifying the potential underestimation of exposure when using the 99 th percentile-based Ei,avg for several representative scenarios of a highly localized magnetic field exposure of the hand using a state-of-the-art anatomical body model. Besides comparing the 99 th percentile-based Ei,avg values with values obtained when using higher percentiles, we also compare with E i,avg values obtained by applying a statistics-based outlier elimination method proposed by Arduino et al. (2020). Our results clearly demonstrate the inappropriateness of the 99th percentile-based assessment, as it may lead to underestimations of the actual induced E i,avg by more than a factor of 100, depending on the exposure scenario. In contrast, the statistics-based artifact elimination strategy proves to be a reasonable and robust method for estimating the actual value Ei,avg for highly localized magnetic field exposure of the hand.