# Model Variability in Assessment of Human Exposure to Radiofrequency Fields

Akimasa Hirata, Ilkka Laakso, Francesca Apollonio, Sachiko Kodera, Yoshiki Kubota, Junqing Lan, Kun Li, Micaela Liberti, Dragan Poljak, Kensuke Sasaki, et al.

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Akimasa Hirata, Ilkka Laakso, Francesca Apollonio, Sachiko Kodera, Yoshiki Kubota, et al. Model Variability in Assessment of Human Exposure to Radiofrequency Fields. IEEE Journal of Microwaves, inPress, 10.1109/JMW.2025.3628902. hal-05423096

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Received 28 September 2025; accepted 31 October 2025.

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# Model Variability in Assessment of Human Exposure to Radiofrequency Fields

AKIMASA HIRATA Ⓔ<fnref n="1" /> (Fellow, IEEE), ILKKA LAAKSO Ⓔ<fnref n="2" /> (Member, IEEE), FRANCESCA APOLLONIO Ⓔ<fnref n="3" /> (Member, IEEE), SACHIKO KODERA Ⓔ<fnref n="1" /> (Member, IEEE), YOSHIKI KUBOTA Ⓔ<fnref n="1" />, JUNQING LAN<fnref n="4" />, KUN LI Ⓔ<fnref n="5" /> (Member, IEEE), MICAELA LIBERTI Ⓔ<fnref n="3" /> (Member, IEEE), DRAGAN POLJAK Ⓔ<fnref n="6" /> (Senior Member, IEEE), KENSUKE SASAKI Ⓔ<fnref n="7" /> (Member, IEEE), MAXIM ZHADOBOV Ⓔ<fnref n="8" /> (Senior Member, IEEE), AND YINLIANG DIAO Ⓔ<fnref n="9" /> (Member, IEEE)

(Invited Paper)

CORRESPONDING AUTHOR: Akimasa Hirata (e-mail: ahirata@nitech.ac.jp).

**ABSTRACT** The recent advances in computational dosimetry for electromagnetics and thermodynamics are reviewed to assess human exposure to electromagnetic fields in the MHz-to-terahertz range. This review emphasizes model variability in computational dosimetry. Apart from computational electromagnetic methods and their usage, the developments in anatomical phantoms and tissue dielectric properties characterization are also surveyed. In addition, the rationale for dosimetric quantities prescribed in international exposure guidelines, such as the specific absorption rate (SAR) and absorbed power density, is revisited in relation to their correlation with local and core temperature rises in various tissues and populations. A heating factor, which is defined as a steady-state temperature rise per SAR, for the brain, eye lens, skin, and body core is evaluated to estimate heating resulting from exposure to electromagnetic fields. The transition of a physical quantity in the guidelines at 6 GHz, from SAR to the absorbed power density, is discussed along with the optimal spatial averaging volume and areas. Computational evaluations of product compliance, 5G devices, and wireless power transfer systems are also reviewed. This review aims to synthesize the current knowledge, identify key sources of computational model variability and uncertainty, and outline further research needs for setting exposure guidelines and compliance assessment.

**INDEX TERMS** Biological effects of radiation, computational electromagnetics, dosimetry.

## I. INTRODUCTION

In protecting humans from excessive exposure to electromagnetic fields (EMFs), exposure guidelines and standards have been published by international standardization bodies. Two international standardization bodies for nonionizing radiation protection have been proposed by the World Health Organization: the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the IEEE International

Committee on Electromagnetic Safety (ICES) Technical Committee (TC) 95.

These guidelines and standards have systematically set and updated exposure limits [1]. The procedure adopted is as follows: peer-reviewed journal papers are reviewed to identify the adverse health effects of EMF exposure and the (operational) threshold is determined for substantiated (established) effects. Considering safety or reduction factors, the limits for

<footnote n="1">¹Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan</footnote>

<footnote n="2">²Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland</footnote>

<footnote n="3">³Department of Information Engineering, Electronics and Telecommunication, Sapienza University of Rome, 00185 Roma, Italy</footnote>

<footnote n="4">⁴College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610103, China</footnote>

<footnote n="5">⁵AWCC, The University of Electro-Communications, Tokyo 182-8585, Japan</footnote>

<footnote n="6">⁶Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia</footnote>

<footnote n="7">⁷National Institute of Information and Communications Technology (NICT), Koganei 184-8795, Japan</footnote>

<footnote n="8">⁸Univ Rennes, CNRS, Centrale Supelec, Nantes Université, IETR UMR, 6164 Rennes, France</footnote>

<footnote n="9">⁹College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China</footnote>
internal physical quantities, which are referred to as basic restrictions (BRs) by the ICNIRP [2] and dosimetric reference limits (DRLs) by the IEEE ICES [3], are derived. The external EMF strengths and power density levels, which are referred to as reference levels (RLs) by the ICNIRP or exposure reference levels (ERLs) by the IEEE ICES, were conservatively derived from BRs or DRLs.

In the case of pulsed exposures with low-frequency EMFs ranging from 0 to 100 kHz and up to several MHz, the primary adverse effect is the stimulation of central and peripheral nervous tissues [3], [4]. By contrast, for radiofrequency (RF) EMFs above 100 kHz, the dominant effect is heating, which is due to Joule loss in tissues.

Dosimetry studies of RF EMFs above 100 kHz have focused on the electromagnetic power absorbed by tissues and the resulting local or core temperature rise. In a tutorial paper, Chou et al. reviewed experimental dosimetry and highlighted the intricate nature of RF dosimetry [5]. The factors influencing power absorption in tissues include the dielectric properties, geometry, and size of the tissue; field orientation and polarization, modulation and waveform, frequency, and source configuration. A discontinuity in the limit was observed at 300 GHz between the RF [2] and infrared guidelines [6], even though the underlying interaction mechanism remains the same across this frequency range.

Computational dosimetry for electromagnetics and thermodynamics using realistic human body models plays a crucial role in deriving thresholds and exposure limits. These dosimetric evaluations are directly linked to the reduction factors applied in international guidelines, as they quantify the variability and uncertainties that the safety margins are intended to cover. In addition, accurate replication of the experimental conditions is essential for determining the limits based on power absorption and temperature rise. Identifying the relevant physical quantities and conditions associated with thermal effects and establishing their correlations with tissue temperature rise are also necessary. RLs (ERLs) are derived from BRs (DRLs) under conservative worst-case assumptions. Furthermore, dedicated computational standards have been developed to facilitate product compliance assessments [7], [8].

Reviews at frequencies above 6 GHz [9] and the IEEE ICES Workshop Report on Computational Bioelectromagnetics [10] have been published previously. However, dosimetry reviews, except for those in a frequency range of >6 GHz, are limited [11], [12]. In addition, reviews on recent advancements in numerical phantom development and compliance assessment are limited in this field.

This review aims to summarize the recent advances in computational dosimetry studies and related standards. In particular, it aims to evaluate how variability in anatomical models affects dosimetric quantities such as specific absorption rate (SAR), power density, and temperature rise, in comparison with uncertainties arising from dielectric properties and computational methods. The scope of this review

is limited to frequencies above 100 kHz, consistent with the range covered by international RF exposure guidelines [2].

## II. COMPUTATIONAL MODELS

### A. TISSUE DIELECTRIC PROPERTIES

The dielectric properties of biological tissues are dispersive quantities, essential to computational dosimetry and electromagnetic exposure assessment. The widely used database in [13], which was derived primarily from comprehensive measurements of more than 50 mammalian tissues below 20 GHz, has served as a universal reference for decades in numerical modeling. Comparative studies have shown that the dielectric properties of mammalian tissues are generally representative of human tissues across the 100 MHz–10 GHz range [14], [15]. A recent comprehensive review can be found in [16]. Building upon such reviews, a comprehensive database of tissue dielectric properties has been constructed to support numerical modeling and exposure assessment [17].

Several factors can influence dielectric properties [18]. Species differences (human versus animal) are relatively small for most tissues in the RF range [14], [15]. However, postmortem changes can lead to measurable deviations, especially in in vitro samples [14], [19]. These changes are related to physiological and biochemical alterations after death, including changes in water content, ion concentration, and membrane integrity. However, the postmortem effect has not been fully characterized partly because of the difficulty in maintaining consistent tissue states during measurement [16]. Aging can also affect dielectric properties through structural and compositional changes, such as reduced water content [20] and altered lipid composition, and it has been incorporated into age-specific numerical models [14], [21], [22], [23], [24], [25].

At frequencies above 6 GHz, where penetration depths are shallow, accurate dielectric data for surface tissues are becoming increasingly important. Measurements have been performed on the skin [13], [14], tissue mimicking phantom [26], and ocular tissues [15], revealing regional variations in skin dielectric properties caused by differences in stratum corneum thickness and underlying dermal structure [14]. At frequencies below 1 MHz, electrode polarization dominates the measurement uncertainty, and its impact has not been fully quantified [16], thereby limiting the reliability of the dielectric data [15], [17].

Recent studies have emphasized the importance of broadband dielectric characterization, improved measurement protocols to minimize electrode polarization and thermal drift, and accounting for physiological variability (e.g., hydration level and anatomical site) when constructing computational models (reviewed in [16], [18]). These refinements are essential for accurate simulations in emerging exposure scenarios, particularly at millimeter wave (mmW) and terahertz (THz) frequencies, where localized interactions with superficial tissues are critical.
<table><caption>TABLE 1. Anatomical Human Models Used for Computational Dosimetry</caption><thead><tr><th>Model name (year)</th><th>Type</th><th>Resolution</th><th>Number of regions</th><th>Number of subjects (adult/child, male/female)</th></tr></thead><tbody><tr><td>HUGO (2002) [31]</td><td>Voxel</td><td>1 mm isotropic</td><td>32</td><td>1 (1/0, 1/0)</td></tr><tr><td>TARO/HANAKO (2004) [35]</td><td>Voxel</td><td>2 mm isotropic</td><td>51</td><td>2 (2/0, 1/1)</td></tr><tr><td>Mazzurana female model (2004) [42]</td><td>Voxel</td><td>2 mm isotropic</td><td>25</td><td>1 (1/0, 0/1)</td></tr><tr><td>NAOMI (2005) [43]</td><td>Voxel</td><td>2 mm isotropic</td><td>41</td><td>1 (1/0, 0/1)</td></tr><tr><td>CNMAN (2007) [32]</td><td>Voxel</td><td>0.16 mm × 0.16 mm × 1.0 mm</td><td>29</td><td>1 (1/0, 1/0)</td></tr><tr><td>HANAKO (pregnant) [44]</td><td>Voxel</td><td>2 mm isotropic</td><td>51 (mother)<br>5 (fetus)</td><td>1 (1/0, 0/1): based on HANAKO</td></tr><tr><td>Katja (2008) [45]</td><td>Voxel</td><td>1.775 mm × 1.775 mm × 4.84 mm<br>2.08 mm × 2.08 mm × 8.0 mm<br>(male)</td><td>153 (mother)<br>18 (fetus)</td><td>1 (1/0, 0/1) based on ICRP adult<br>female model</td></tr><tr><td>ICRP 110 (2009) [38]</td><td>Voxel</td><td>1.875 mm × 1.875 mm × 5.0 mm<br>(female)<br>0.5 mm × 0.5 mm × 1.5 mm<br>(heart)</td><td>141</td><td>2 (2/0, 1/1)</td></tr><tr><td>Virtual Family (2009) [33]</td><td>Voxel</td><td>0.9 mm × 0.9 mm × 2.0 mm<br>(others)<br>0.33 mm × 0.33 mm × 1.0 mm<br>(male)<br>0.33 mm isotropic (female)</td><td>80</td><td>4 (2/2, 2/2)</td></tr><tr><td>XCAT phantom (2010) [58]</td><td>Voxel</td><td>0.5 mm isotropic (upsampled)</td><td>120</td><td>3 (3/0, 2/1)</td></tr><tr><td>Virtual Population 3.0 (2014) [34]</td><td>Voxel</td><td>-</td><td>120</td><td>11 (4/7, 6/5)</td></tr><tr><td>VHP-Female 2.0 (2015) [36]</td><td>Mesh</td><td>-</td><td>190</td><td>1 (1/0, 0/1)</td></tr><tr><td>Adult Computational Phantoms (2019) [37]</td><td>Voxel</td><td>2.08 mm × 2.08 mm × 8 mm<br>(male)<br>1.875 mm × 1.875 mm × 5 mm<br>(female)</td><td>140</td><td>479 (479/0, not specified)</td></tr><tr><td>ICRP 145 (2020) [39]</td><td>Mesh</td><td>-</td><td>58</td><td>2 (2/0, 1/1)</td></tr><tr><td>XCAT 3.0 (2025) [40]</td><td>Voxel + Mesh</td><td>1.5 mm isotropic, 0.625 mm × 0.625 mm × 3.75 mm</td><td>140</td><td>2528 (2528/0, not specified)</td></tr></tbody></table>

## B. COMPUTATIONAL PHANTOMS

Computational human models play an essential role in various fields that are related to human exposure to EMFs, including protection, product compliance testing, and biomedical applications [27], by assessing physical and physiological effects [28]. In the early stages of research, these models were primarily represented using simplified geometrical shapes [29]. However, they have evolved into high-fidelity models that precisely replicate anatomical structures. In general, these computational models are provided in voxel format or other formats that are compatible with simulation environments, and they are commonly constructed by identifying tissues and organs through the segmentation of medical imaging data.

Many numerical human models have been developed and used for EMF analysis, and they have exhibited considerable diversity with regard to anatomical fidelity, imaging modality, subject demographics, such as age and sex, and the number of segmented tissues. Prior to 2000, models with a relatively coarse resolution along the body axis, typically 5–10 mm [30], were commonly used. Since 2000, the development of high-resolution models advanced significantly. Apart from the increased anatomical detail, efforts have been made to enhance the structural and practical aspects of human models, including the expansion of organ types, improved statistical representativeness based on multiple subjects, and greater compatibility with numerical simulations spatial discretization (e.g., mesh generation or voxelization).

The characteristics of representative human models developed after 2000 are summarized in Table 1.

The HUGO model [31] is one of the earliest high-resolution adult models, which has a 1-mm isotropic resolution and a detailed anatomical representation. The CNMAN model [32] was generated from a Chinese adult male, which features an exceptionally high anatomical resolution of 0.16 mm. Virtual Family [33] and Virtual Population 3.0 [34] provide models that reflect different ages, sexes, and body types, and they have been used in the formulation of international exposure guidelines. The TARO and HANAKO models [35], which represent the anatomical features of Japanese adults, have been widely used for dosimetric assessments. VHP-Female 2.0 [36] provides a single female model with an exceptionally high level of anatomical detail, comprising 190 segmented regions and supporting mesh-based simulations. In addition, the Adult Computational Phantom [37] provides 479 body models derived from the ICRP voxel model [38], [39], offering a comprehensive anatomical basis for various dosimetric evaluations. More recently, XCAT 3.0 [40] was developed as a model library constructed from CT images of more than 2500 patients. It maintains detailed organ information and supports mesh generation, thereby providing high flexibility and applicability.

The development of anatomically realistic female human body phantoms has been pivotal in extending computational dosimetry beyond male-based references [41]. An early work
[42] demonstrated the feasibility of constructing a female RF dosimetry phantom directly from MRI data, enabling more accurate estimation of gender-specific SAR distributions. Building on this, a detailed female voxel phantom was developed [43]. Subsequent efforts expanded to pregnant female models [44]. Further studies introduced specialized gestational-stage models such as Katja, representing a 24-week pregnancy for dosimetric calculations [45]. Collectively, these phantoms address physiological and anatomical differences critical for accurate safety assessments in women and developing fetuses.

On the contrary, high-resolution and multi-tissue head models such as MIDA [46] and CMODEL [47] have been used for head EMF analyses to assess exposure, brain stimulation, and conductivity mapping. Furthermore, SHARM [48], which was developed on the basis of a large number of adult subjects with varied anatomical characteristics, enables reliable studies in electromagnetic dosimetry and human safety.

In recent years, the development of highly accurate segmentation techniques based on artificial intelligence, particularly deep learning [49], [50], as well as the increasing availability of subject-specific model generation tools [51], [52], [53], has led to a shift from standardized anatomical models to personalized ones. However, methods that assign conductivity values to segmented anatomical regions have inherent limitations, including the propagation of segmentation errors into conductivity assignment and the inability to represent spatially nonuniform conductivity within a given tissue, as a uniform value is typically assigned to each region. Thus, several segmentation-free conductivity estimation methods have been proposed to address these limitations [54], [55]. The proposed methods can estimate conductivity distributions without being affected by segmentation errors [2], while allowing the representation of individual variability and spatial heterogeneity. Personalized models incorporating such nonuniform conductivity distributions can improve the accuracy of electric field simulations [50], [56]. Thus, their further implementation and clinical application are anticipated [57].

### C. SUPERFICIAL TISSUE MODELING

At frequencies above 6 GHz, electromagnetic dosimetry is influenced by skin modeling caused by the shallow penetration depth of RF energy (4 mm at 6 GHz, 2 mm at 10 GHz, and 0.4 mm at 30 GHz) [59], [60]. Most anatomical models (see Section II-B) are derived from medical imaging with original resolutions of a few millimeters, thereby limiting their ability to represent a detailed skin morphology. Although some CAD-based anatomical models allow adjustable resolution [34], the accuracy of the rescaled geometry remains uncertain on anatomical data [61], realistic modeling of skin thickness variation can improve dosimetric accuracy. The skin is a multilayered structure comprising the epidermis, dermis, and hypodermis, which contains sweat gland ducts, nerves, oil glands, and blood vessels. Multilayer computational models have been used to examine mmW and THz heating effects. Recently, a 3D skin segment containing sweat gland ducts was

modeled [62]. The model incorporated the detailed morphology of cutaneous appendages, including nerves, lymphatics, pilosebaceous units, microvasculature, eccrine sweat glands, and sensory corpuscles, based on morphometric data and microscopic images [62], [63]. The tissue-specific dielectric properties were estimated using Maxwell's and mixture equations derived from the reported free water content. A recent study also proposed a reference skin model in the 6–100 GHz range for the experimental phantoms design and absorbed power density evaluation [64].

### III. COMPUTATIONAL METHODS

#### A. SUB-6 GHZ BAND

At frequencies above 10 MHz, volume-based full-wave analysis methods, particularly the finite-difference time-domain (FDTD) [65] and finite element (FEM) [66] methods, are typically used to capture EMF interactions in heterogeneous biological tissues. Surface-based approaches, such as the method of moments (MoM), can also be used, but they are less suitable for modeling heterogeneous structures.

At frequencies ranging from MHz to THz, which is the scope of this paper, the primary health concern is thermal effects, particularly tissue heating caused by energy absorption. The most relevant dosimetric quantity in the range from 100 kHz to 6 GHz, is the SAR [W/kg], which quantifies the rate at which electromagnetic energy is absorbed per unit mass of tissue. Peak spatially averaged SAR averaged over 10 g of tissue (psSAR<sub>10g</sub>) and whole-body averaged SAR (WBASAR) are used as physical quantities, thereby limiting the spatial peak and core temperatures.

Computational dosimetry in this frequency band typically relies on the FDTD and FEM approaches. The FDTD method is widely used because it can easily accommodate voxel-based anatomical models and account for inhomogeneous tissue properties; this method is also highly amenable to parallel computations [65]. The FEM provides flexibility for complex geometries and unstructured meshes, making it suitable for human models with curved boundaries [66]. Alternative methods, such as the finite integration technique (FIT) and the transmission line method, are also used, particularly in compliance testing. These methods have contributed to the derivation of BR (SAR-based limits) and associated RLs or ERLs in the current exposure guidelines and standards [2], [3].

Notably, domain decomposition (i.e., differential equation) approaches such as FDTD and FEM have advantages with regard to robustness and relative algorithmic simplicity, but they also suffer from drawbacks such as staircasing error (FDTD) and problems with unbounded domains (FDTD and FEM).

On the contrary, when using boundary discretization (i.e., integral equation) approaches such as MoM or boundary element methods (BEM), volume meshes or the implementation of absorbing boundary conditions (ABC) is not necessary, and staircasing error is avoided because of the use of isoparametric elements [67]. However, these methods have significant drawbacks, including complex formulation and numerical
<figure><img src="image_3.png" /></figure>

implementation, Green's function singularities/quasi-singularities, and higher computational resources when compared with FDTD and FEM. Over the recent decades, hybrid approaches such as coupled MoM/FEM and BEM/FEM emerged as efficient methods for solving problems in computational bioelectromagnetics taking the best from differential and integral approaches. However, they inevitably end up in rather complex formulations [68].

More advanced or hybrid techniques, such as FEM/MoM and FDTD/MoM, have been used to combine the strengths of volume-based and surface-based methods. These hybrid methods are particularly useful for solving problems that involve interactions between the human body and external antennas or devices [69], [70]. These approaches are mainly used for product assessment, such as verifying the compliance of induced SAR with exposure limits or optimizing antenna design.

A coupled edge-element BEM/FEM approach to analyze the electric field induced inside the human head caused by plane wave exposure has been previously reported [71]. The operating frequency is 3.5 GHz, which corresponds to 5G cellular networks. A trade-off between the BEM/FEM and MoM/FEM approach is given in the paper.

## B. MILLIMETER-WAVE AND TERAHERTZ BAND

For frequencies above 6 GHz, particularly in the mmW range, EMFs penetrate only the epidermis and dermis. Consequently, surface heating is the predominant effect, and SAR is no longer appropriate. Instead, absorbed power density (APD) and epithelial power density (EPD) [2], [3] are used, whereas incident power density (IPD) in free space serves as the RL or ERL for compliance testing. Although the WBASAR limit in the ICNIRP guidelines has been extended up to 300 GHz, local exposure assessments focus on the accurate estimation of surface power absorption.

Early investigations used one-dimensional (1D) and later two-dimensional (2D) stratified skin models to analyze power absorption [72], [73] and the effect of oblique incidence [74], [75]. The transmission factor depends on incident angle, especially for TM polarization beyond Brewster's angle [74], [75], whereas normal incidence generally represents the conservative scenario.

For near-field exposure, the FDTD method has been widely applied to planar and curved skin models up to ~100 GHz [60], [76], [77]. Compared with the sub-6-GHz range, where exposure is dominated by nearby antennas, frequencies above 6 GHz may involve larger source-body separations due to beamforming and localized hotspots. In assessing such conditions efficiently, hybrid approaches such as ray-tracing/FDTD, MoM/fast multipole [78], and spherical wave expansion/FDTD [79] have been developed.

In the far field, where the wavelength is smaller than the body dimensions, APD can be estimated by multiplying free-space IPD with the transmission factor of the plane wave, which is mainly determined by the skin model (see Section II-C) [80]. In capturing small-scale variations near the

surface, FDTD or FIT method with a fine resolution has been applied.

In this band, accurate simulation requires a fine voxel resolution and a mesh quality near the tissue-air interface due to shallow penetration and steep gradients. Recent studies have shown the applicability of voxel-based methods [81]. By contrast, BEM and MoM are less common in mmW dosimetry because of the high computational cost for complex heterogeneous bodies [82]. However, hybrid methods are still explored for cases where device-body coupling is critical.

## IV. PHYSICAL QUANTITIES USED IN GUIDELINES: COMPUTATIONAL BASIS AND RATIONALE

As heating is the substantiated effect in this frequency range >100 kHz, a multiphysics approach was adopted. This section reviews the role of computational dosimetry in setting the physical quantities used in international guidelines.

### A. SAR AVERAGED OVER 10 G OF TISSUES

International guidelines and standards adopt $psSAR_{10g}$ as a metric because of its ability to provide a strong correlation with the spatial peak temperature rise. Notably, a spatial peak temperature rise appears around the surface but not always at the surface [83]. This correlation has been examined in several studies using different averaging masses and schemes. For example, previous studies [84], [85] demonstrated that 10 g averaging shows a stronger correlation with a steady-state temperature rise than 1 g averaging. Similarly, the optimal averaging mass has been reported to lie between approximately 8 and 20 g, which remains effective for frequencies up to 6 GHz [86]. The primary determinant of this optimal range is the thermal diffusion length, which is strongly influenced by the blood perfusion rate of the tissue and the penetration depth of the incident RF fields.

The influence of different averaging schemes was also studied, and the findings revealed that the averaging mass has a greater correlation with temperature rise than the shape of the averaging volume, with cube- and sphere-based schemes providing comparable results [87]. Furthermore, several studies [85], [88], [89] confirmed that 10 g averaging remains a reliable predictor of local temperature rise, even under whole-body exposure conditions.

### B. AREA-AVERAGED APD

At frequencies above 6 GHz, the shallow penetration depth makes SAR (10 g) unsuitable for assessing local heating. In this regime, APD at the surface is a more reliable metric, which correlates well with temperature rise and is less sensitive to frequency and exposure conditions [90], [91].

The ICNIRP guidelines recommend two equivalent formulations: the integration of (1) SAR along depth multiplied by mass density and (2) the real part of the complex Poynting vector over a defined averaging area. These formulations yield nearly identical results for flat surfaces, but they may differ slightly in more complex skin models because of averaging schemes.
The averaging area for APD/IPD has been studied in relation to thermal diffusion length. Optimal values of 2–4 cm² (≈7 mm diffusion length) were reported [72], [92] at frequencies > 6 GHz; 4 cm² roughly corresponds to the surface area of a face of the 10 g cube. At frequencies above 10 GHz, using a 4 cm² average predicted temperature rises that are consistent with 1D or plane-wave exposures [92]. At mmW frequencies, where the irradiated spot may be <4 cm², reducing the averaging area improved the correlation with spatial peak skin temperature, which motivated the current guideline's additional 1 cm² limit above 30 GHz [93].

Intercomparison studies conducted by IEEE ICES TC95/SC6 using curved models (cylinders and spheres) confirmed that spatially averaged APD over 4 cm² strongly correlated with spatial peak temperature rises, whereas smaller areas improved correlation at higher frequencies such as 90 GHz [94]. Geometry also influenced averaging: The differences between the two schemes reached ~20% at 6–10 GHz with small radii but dropped below 10% at above 20 GHz with larger radii. The effect of averaging shape (square versus circular) was minor (<5%), except at very close source–body distances [95], [96].

### C. WHOLE-BODY AVERAGED SAR

The rise in body core temperature under uniform RF exposure was examined in different populations, including adults, children, fetuses, and elderly individuals, as well as under varying environmental and clothing conditions. Thermoregulatory mechanisms, including sweating and vasodilatation, are key factors limiting the rise in core temperature, and spatiotemporal variation in blood temperature must be considered for accurate modeling.

For healthy adults, the required WBASAR to increase the core temperature by 1 °C within approximately 1 h typically ranges from 4 to 6 W/kg [97], [98]. The dominant factor characterizing the temperature is the body surface-to-mass ratio, which is larger in adults than in children. With regard to exposure at the RL for the general public, the computed rise in core temperature was 0.014 °C [99].

## V. MODEL VARIABILITY AND COMPUTATIONAL UNCERTAINTY IN SAR EVALUATION

This section reviews model variability in SAR as reported in the literature. The number of APD study is still limited to summarize the data, and thus this aspect is discussed in detail in Section VII, together with case studies on wireless devices.

### A. SAR AVERAGED OVER 10 G OF TISSUES

Computational comparisons of adult and child head models have been extensively reviewed [100]. Overall, psSAR₁₀g during mobile phone use does not differ substantially between children and adults, although a smaller head size and anatomy can produce higher localized SAR in certain regions. These effects are relevant to dosimetry but not directly to compliance metrics, which rely on psSAR₁₀g.

Thus, this section focuses on the intermodel variability of psSAR₁₀g in studies using three or more anatomical models. For example, in [101], psSAR₁₀g at 900 MHz was assessed in three adults and one synthetic model, showing ~13% variability and a max-to-min ratio of ~1.3, which indicates the influence of anatomical geometry on localized peaks. In addition [102], four adults, two children, and scaled child models exposed at 835 and 1900 MHz yielded coefficients of variations (CVs) ranging from 12% to 28% and max-to-min ratios of 1.3–1.9, highlighting the impact of head size and scaling methods. In [103], six adults and seven children exposed to 900–2100 MHz exhibited broader variability, with CVs ranging from 10% to 62%, and morphing techniques further emphasized sensitivity to head morphology. In [104], five homogeneous adult head phantoms exposed to 900–1950 MHz produced psSAR₁₀g CVs of 9%–20% and max-to-min ratios of 1.2–1.8, underlining the role of geometry.

The largest dataset was reported in [105], which analyzed 20 adult models at 835 and 1900 MHz. They reported CVs of 21%–35% and max-to-min ratios of 2.5–3.1 for psSAR₁₀g, providing the most robust estimate of variability across realistic head anatomies. In [106], four adults and five children exposed to phones at 900–1950 MHz showed additional differences depending on the phone position and hand presence, with max-to-min ratios between 1.0 and 2.0, although CV values were not reported.

In summary, all studies consistently demonstrated variability in psSAR₁₀g across the anatomical models. Although small-sample studies (≤6 models) showed CVs typically below ~30% with limited reliability, the larger dataset [105] indicates that interindividual anatomical variability in psSAR₁₀g is on the order of ~30%, with rare extreme cases producing up to threefold differences.

### B. WHOLE-BODY AVERAGED SAR

Multiple studies have shown that children exhibit higher WBASARs than adults. In [107], [108], infant and child models (9 months–14 years) exposed to 50 MHz–2.45 GHz had 40%–50% higher WBASARs than adults, with additional dependence on incidence angle. Other investigations further highlighted anatomical and physiological factors: For example, in [109], variation with incidence direction and an inverse correlation with BMI led to higher WBASARs in children; in [110], empirical formulas linked WBASAR to body size. Using realistic ICRP-based models (1–10 years), a previous study [111] reported 40%–60% higher WBASARs than adults, whereas homogeneous scaling underestimated variability by 20%–30%. Similarly, thin body types (~10th percentile weight) exhibited ~20% higher WBASARs, whereas age-dependent dielectric properties contributed a <6% variation [112].

Variability is also influenced by the construction method and internal morphology of the models. In [113], child models (3–7 years) generated by nonlinear scaling differed by <15% from simply scaled models, highlighting the influence of modeling approaches. In [114], a predictive formula linked
<figure><img src="image_4.png" /></figure>

resonance SAR to body size, with variability of ~10% from dielectric properties and 30% from body-shape differences within the same age group. Similarly, analysis of 30 anatomical models and 18 morphed phantoms at 2.1 GHz showed that internal factors such as the muscle-to-fat ratio significantly affected SAR, whereas regression models predicted WBASAR with ~10% error [94].

In [115], an infant model was exposed to 50 MHz–4 GHz with estimated newborn dielectric properties; the WBASAR at resonance was 15% higher than that for an adult, although the relationship reversed at higher frequencies because of high conductivity and shallow penetration depth. In [116], the effect of polarization was analyzed, showing that it strongly influenced WBASAR; in the 2–5 GHz range, horizontally polarized fields produced WBASAR values up to 60% higher than vertically polarized fields in adults. In [117], a 12-month-old infant and an adult female model were evaluated at 3.5 GHz; the differences in SAR caused by age-dependent dielectric properties accounted for <6%, and embracing or carrying configurations changed SAR by only 5%–7%, with infant absorption not exceeding that at 1.9 or 2.4 GHz.

In FDTD simulations, the IEC/IEEE standard specifies the criteria for numerical uncertainty [7], including voxel resolution, positioning, convergence, and ABCs. The voxel size must be smaller than one-tenth of the wavelength in the tissue, keeping the WBASAR variation within ±10% under plane-wave exposure [107], [118], [109]. At higher frequencies and coarser grids, discrepancies also arise from SAR computation algorithms [76]. ABCs, such as split-field, uniaxial, or convolutional PML, can produce errors of up to 10% [119], which can increase to 15%–20% under unfavorable conditions [120], [115], [121] but can be reduced by proper parameter control.

In summary, WBASAR in child and smaller models was 40%–60% higher than that in adults. Additional variability arises from body shape, modeling methods, and tissue composition (10%–30%), whereas factors such as polarization or incidence angle can increase SAR by up to ~60%. For a reliable interstudy comparison, the SAR calculation algorithm and boundary conditions used must be explicitly stated.

# VI. MODEL VARIABILITY IN TEMPERATURE RISE

## A. TEMPERATURE RISE IN THE BRAIN (<6 GHZ)

Numerous computational studies have quantified the heating factor, which is defined as the brain temperature rise per unit psSAR₁₀g under localized exposure from various antenna types and frequencies. A discrete vessel model was used to incorporate arterial heat exchange, reporting heating factors of 0.095–0.12 °C·kg/W [122], which were lower than the conventional bioheat estimates. For multiple handset antennas (0.9–1.9 GHz), similar heating factors were found across antennas and scenarios: 0.020–0.12 °C·kg/W [123]. In [124], comparable heating factors of 0.10–0.115 °C·kg/W were observed in adult and child models (0.8–2.45 GHz). A strong

dependence on the thermal parameters was also confirmed, with a maximum heating factor of 0.12 °C·kg/W [125].

At higher frequencies, heating factors of 0.04–0.12 °C·kg/W have been reported, which indicates that the 10 g-averaged SAR remains a valid surrogate for brain heating up to ~3–4 GHz [126]. Considering its impact when temperature rises exceeded 2 °C, thermoregulatory vasodilatation estimated that SAR values above 100 W/kg would be necessary to raise the brain temperature to 43 °C (0.3–10 GHz) [127].

Stochastic thermal dosimetry of a realistic head model exposed to plane-wave radiation at 3.5 GHz was performed using stochastic collocation, which shows that scalp and brain blood perfusion rates are the dominant factors governing the uncertainty of temperature rise [128], consistent with the findings from deterministic approaches [129].

In summary, the brain heating factors for 10 g-averaged SAR generally fall below 0.12 °C·kg/W. Under the occupational exposure limit of 10 W/kg [2], [3], this value corresponds to a brain temperature rise of 1 °C or less in most scenarios. Thermal properties, particularly blood perfusion around the brain, are key determinants of these values.

## B. TEMPERATURE RISE IN THE EYE LENS (<6 GHZ)

Computational and experimental studies have investigated the heating factor in the human lens, which is defined as the temperature rise per unit SAR, across a frequency range of sub-gigahertz to several gigahertz. Most studies have used eye-averaged SAR (with a mass of approximately 7–11.5 g) in accordance with previous guidance [130], whereas others have used 10-g cubic averaging volumes that included the eye. For the eye-averaged SAR, the reported heating factors generally range from approximately 0.09 to 0.19 °C·kg/W for frequencies below 6 GHz, with some higher values up to 0.30 °C·kg/W in specific cases (e.g., [131], [132]). Notable examples include 0.15–0.17 °C·kg/W [133], 0.093–0.14 °C·kg/W [134], 0.18–0.19 °C·kg/W [135], and 0.11–0.15 °C·kg/W [136]. For the 10-g cubic SAR, heating factors were generally lower, mostly ≤0.16 °C·kg/W, such as 0.12–0.15 °C·kg/W [137], 0.083–0.15 °C·kg/W [138], and 0.090–0.16 °C·kg/W [132]. Some studies have reported a gradual increase in heating factors above approximately 3 GHz, although the values remained below ~0.157 °C·kg/W for frequencies below 6 GHz. In some cases, incorporating thermoregulatory responses, such as vasodilatation and blood perfusion in the choroid/sclera, substantially reduced heating factors by 30%–50%, with reported values of 0.036–0.084 °C·kg/W at 2.45 GHz [139].

In the absence of thermoregulation, the lens heating factor for psSAR₁₀g is at most ~0.1 °C·kg/W in typical scenarios, which corresponds to the maximum lens temperature rise of approximately 1 °C under the occupational [2] or controlled exposure [3] limits of 10 W/kg. This value is well below the threshold for cataract formation, and under realistic overexposure conditions, heating of the surrounding facial skin is the dominant concern.
In summary, the variability in lens heating factors arises from the choice of averaging scheme (eye-averaged versus 10-g cubic) and the inclusion of thermoregulatory responses, which can reduce the predicted values by up to 50%, whereas detailed evaluations using child-specific eye models remain limited.

### C. TEMPERATURE RISE IN THE SKIN (>6 GHZ)

The EPD/APD in head models was computed with a spatially varied skin thickness at 1–100 GHz, reporting that realistic variation suppressed strong standing waves, thereby reducing the averaged EPD/APD by up to ~20% (4 cm²) and ~10% (1 cm²) compared with uniform-thickness models [80].

An approximate formula was derived for the steady-state skin temperature rise in a 1D three-layer model (skin, fat, and muscle) exposed to 30–300 GHz plane waves, incorporating a Debye-type approximation for dielectric dispersion [140]. Thermal constants and tissue thickness were found to have a greater impact on heating than dielectric properties, with temperature rise correlating more with total absorbed power than with IPD. In a follow-up study [141], one-layer and three-layer models were compared, and the result showed spatial peak rises of 1.1 °C at 30 GHz and 1.9 °C at 300 GHz (50 W/m²), with the three-layer model yielding 1.3–2.8 times higher surface temperatures because of the adiabatic effect of the fat layer. The heat transfer coefficient was identified as the dominant factor.

A thick stratum corneum acts as a matching layer, which can reduce mm-wave reflection [142]. In [143], a four-layer (epidermis, dermis, subcutaneous tissue, and muscle) skin model for temperature rise was used in 10 GHz–1 THz exposure, and individual variability in tissue thickness was found to cause 8%–11% variation at a steady state. In addition, the impact on the variance due to tissue dielectric properties had less impact on the temperature rise compared to the variability due to tissue thickness. Furthermore, the transmission coefficient at skin surface increases with frequency, resulting in higher power absorption.

Fine-scale structures such as sweat gland ducts can concentrate electromagnetic energy and produce localized SAR hotspots [144]. For exposure at 94 GHz, such hotspots were observed inside and around the ducts, but the corresponding steady-state temperature rise was modest, remaining <10% higher than that in the surrounding tissue. The temperature rise in cutaneous nerves and capillaries was computed at 60 GHz, showing a spatial peak power density that is 30% higher than that of the surrounding skin [63].

In summary, variability in skin heating mainly reflects differences in tissue thickness, multilayer structure, and microstructural features, which simultaneously influence both average absorption and local hotspots.

### D. TEMPERATURE RISE FOR BRIEF PULSE

In [2], [3], the RF exposure limits for brief pulses were revised. The current restrictions for brief exposure are provided as the permissible energy fluence (integral of the EPD/APD),

which is a function of the pulse duration based on the early transient response of temperature. The surface temperature rise was evaluated for brief pulse exposures [77], [145], [146], [147], [148]. In [145], the temperature rise for brief pulses and pulse trains was demonstrated. In [77], the effect of exposure duration on temperature rise was investigated in a human face model with a 100-µm resolution. The surface temperature showed a steeper initial transient response, particularly at frequencies >20 GHz. Hotspot absorption in complex structures may result in higher temperature rises than those in 1D or planar models. In [149], the temperature increase at the skin surface exposed to an RF pulse train was computed using a 1D baseline model. The temperature rise induced by a mmW RF pulse exhibits sharp peaks because of the short-term accumulation of heat near the surface; however, the heat is progressively conducted to deeper tissue layers, and it dissipates rapidly. In [148], a 1D thermal model was demonstrated to provide a useful baseline and agree moderately well with 3D simulations and experimental data. Pulsed heating in skin sub-structures was investigated in [63]. The model showed that differences in anatomy, energy absorption patterns, and tissue properties can lead to notable deviations between the models and measurements.

In summary, the variability in the predicted temperature rise induced by brief pulses is mainly associated with surface heating, where simplified 1D models capture the initial response but differ from 3D anatomical simulations because of anatomical and tissue property heterogeneity.

### E. TEMPERATURE RISE IN BODY CORE

Children generally exhibit a 30% smaller core temperature rise than adults at the same WBASAR, for example, a 0.03 °C rise at 0.08 W/kg in a 3-year-old model [150].

Fetal heating strongly depends on the maternal thermal status. A model that incorporated placental heat exchange showed that the fetal core temperature is ~0.5 °C higher than the mother's baseline [151] and increases by an additional ~30% of the maternal increase in temperature under EMF exposure [152]. Older individuals may experience greater core temperature rises because of reduced sweating capacity [152].

Environmental and clothing factors outweigh the effects of EMF-induced heating in occupational scenarios. Under high humidity, high ambient temperature, and heavy clothing, the additional thermal load from EMF exposure at occupational limits is relatively small [153], [154]. For example, at 4 W/kg WBASAR, the maximum observed rise was 0.9 °C, whereas at 0.4 W/kg over 0.1–6 GHz, the rise was ≤0.1 °C.

At frequencies above several gigahertz, superficial energy deposition limits the core temperature rise, and local temperature elevations become more relevant even in whole-body exposure scenarios. For high local exposures (>20 W/kg, 10 g-averaged SAR), the local thermoregulatory capacity largely determines the resultant tissue heating [155].

WBASAR is affected by skin thickness below 20 GHz, and the WBASAR values in unsmoothed anatomical models are 10%–17% higher than those in smoothed models [76].
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>TABLE 2. Summary of Model Variability and Dominant Factors in SAR and Temperature Rise</figcaption></figure>

<table><thead><tr><th>Category</th><th>Parameter / Condition</th><th>Range of Variability</th><th>Dominant Factors / Notes</th></tr></thead><tbody><tr><td rowspan="3">SAR Variability</td><td>psSAR10g</td><td>~30% inter-model; up to 3× in extremes</td><td>Head size, anatomical differences</td></tr><tr><td>WBASAR</td><td>Children 40–60% higher than adults; +10–30% from body shape/tissue properties</td><td>Body size, shape, modeling method</td></tr><tr><td>Polarization & incidence<br>Numerical uncertainty</td><td>Up to ~60% variation<br>Typically, ±10–20% if not controlled</td><td>Field orientation, exposure geometry<br>Mesh resolution, boundaries, algorithm</td></tr><tr><td rowspan="3">Temperature Rise</td><td>Brain & eye (per psSAR10g) (&lt; 6 GHz)</td><td>0.12–0.19 °C·kg/W</td><td>Limited age differences, perfusion important</td></tr><tr><td>Skin (&gt; 6 GHz)</td><td>10–20% variability</td><td>Tissue thickness, microstructure; transient effects in pulses</td></tr><tr><td>Core temperature</td><td>Children smaller; fetuses/elderly larger; environment dominates</td><td>Body shape, Thermal physiology, clothing, environment</td></tr><tr><td rowspan="3">Dominant Influences</td><td>SAR (&lt; 6 GHz)</td><td>Anatomical scaling, body size</td><td>Structural differences drive most SAR variability</td></tr><tr><td>Local temperature rise</td><td>Thermal and physiological parameters</td><td>Blood perfusion and thermoregulatory responses more critical than body size</td></tr><tr><td>Core temperature rise</td><td>Body shape and sweating</td><td>Body surface-to-mass ratio and thermoregulatory responses</td></tr></tbody></table>

However, its impact on the core temperature rise has not yet been investigated, and it remains a topic for future research.

In summary, variability in core temperature rise is driven by body morphology and physiology, with children showing smaller increases, fetuses and the elderly showing greater susceptibility, and additional influences from skin thickness modeling and environmental factors.

## VII. RECENT ASSESSMENT FOR WIRELESS DEVICES

### A. WIRELESS POWER TRANSFER SYSTEM

Wireless power transfer (WPT) systems can be classified into near-field and far-field types based on their coupling mechanisms and operating frequencies. In general, in far-field and narrow-beam WPT, assessment is conducted to compare the RL of exposure guidelines.

Near-field systems can be classified into inductive coupling (IC) and magnetically coupled resonant (MCR) types, which typically operate from a few kilohertz to several megahertz. Such technologies have been implemented in practice, for example, in the wireless charging of electric vehicles (EVs) and various household devices. Although WPT for implanted medical devices [156] is outside the scope of compliance assessments defined in international exposure guidelines such as those of ICNIRP, it remains a subject of considerable interest because of its relevance for power transfer efficiency. In the present review, attention has been directed toward frequencies ranging from megahertz to terahertz; consequently, EV WPT [157], which is standardized at 85 kHz, is not considered here.

IC-WPT primarily uses the magnetic interaction between two coils to transfer power over short distances, usually only a few centimeters. Typically, the frequency of WPT systems is below 100 kHz, but 140 kHz was considered in [158]. In the study, SAR and in situ electric fields were analyzed for a 140-kHz inductive WPT system with two coils and magnetic sheets. Evaluations with three whole-body anatomical models showed the chest region as most restrictive for compliance. Anatomical differences caused ~13% variability,

whereas variation in tissue conductivity contributed up to 30% uncertainty.

In [159], local and whole-body averaged SAR at 10–12 MHz were evaluated for a resonant WPT system using a homogeneous cylindrical phantom and an anatomical whole-body model. The quasi-static approach was validated, with psSAR10g differing by only 4%–8% from full-wave analysis. The chest was the compliance-limiting region, which the simplified cylinder could not capture. In [160], dosimetry for a 10-MHz MCR-WPT system was performed using an anatomical human model. The quasi-static approximation showed that neglecting incident electric fields causes minor differences (<1%) in the skin for central torso exposure and large discrepancies (up to 70%–100%) in the peripheral regions. In [161], [162], a printed midrange high-frequency WPT system (~10 MHz) was assessed using an anatomically detailed model. The results showed that the compliance metrics (E-field percentile, current density, and SAR) did not coincide spatially, indicating that no single metric was sufficient. This result emphasizes the need for a multimetric evaluation when assessing practical WPT designs due to the intermediate range values of the working frequency.

In [163], the SAR and induced electric fields were evaluated for MCR-WPT systems near 8 MHz using four anatomical body models (two adults and two children). Local SAR was shown to be the most restrictive metric, with intermodel variability exceeding 3 dB, depending on body size and anatomy. In addition, a simplified cylindrical phantom was shown to provide conservative estimates that are comparable to those of anatomical models. In [164], the local SAR was evaluated for a 6.78-MHz resonant WPT system using adult and child anatomical models with different coil configurations. The results showed that the adult model exhibited higher localized SAR than the child model, and that the standing posture increased SAR by 20%–30% compared with the sitting posture. The number of receiving coils (1 or 2) only marginally affected exposure outcomes.
In [165], the local SAR was evaluated for near-field WPT systems at 100 kHz, 6.78 MHz, and 13.56 MHz using simplified phantoms and a realistic homogeneous human model. The results showed that the simplified models reproduced the torso SAR within approximately 10%–13% of the realistic model, although localized differences appeared in regions such as the neck and limbs.

In summary, for near-field WPT systems, the computational results showed notable variability: Anatomical differences contributed approximately 10%–20%, whereas tissue conductivity assumptions contributed up to ~30% to the local SAR computation, depending on the scenario.

## B. 5G/6G WIRELESS TERMINALS

Several studies have been conducted to highlight the variability across antenna and human anatomical models as well as the uncertainty in exposure assessment methods for wireless terminals at a frequency of >6 GHz.

In [166], exposure from an eight-element phased-array patch antenna at 27 GHz was studied using homogeneous and multilayer skin models. The homogeneous model underestimated the APD by up to 55%, highlighting the strong influence of tissue representation on the outcome. In [167], exposure was evaluated in adult and child anatomical models in realistic usage scenarios of mobile communications at 28 GHz. The results showed that children experienced higher localized APD than adults, illustrating the mechanism by which body size and anatomical features can substantially affect compliance results. These findings underscore the importance of age-specific models for reliable compliance assessment at mmW frequencies. In [60], dosimetry was conducted to examine the impact of model accuracy at 28 GHz, and the result showed that multilayer slab models may not fully capture the spatial variations observed with anatomically detailed models. In [168], dosimetry was conducted for wearable patch antenna arrays operating at 28 and 39 GHz. This study analyzed four different skin models: homogeneous dermis, two-layered (SC and dermis), (iii) three-layered (SC, dermis, and fat), and (iv) four-layered (SC, dermis, fat, and muscle) models. The distribution of the APD was shown to strongly depend on the antenna configuration and placement on the body, indicating that the device design can be a key factor causing variability in localized exposure.

Similarly, studies considering simultaneous exposure from multiple antennas [169] or realistic handset usage scenarios at 60 GHz [170] further confirmed that antenna configuration, placement, and operating conditions strongly influence local absorption patterns, although certain factors, such as dry versus wet skin, had only marginal effects.

In addition, the evaluation of patch antenna arrays at 10–100 GHz [171] indicated that the conventional 20 mm × 20 mm averaging area may underestimate localized exposure at higher frequencies, and that a smaller 10 mm × 10 mm averaging provides a more conservative assessment.

Stochastic analysis of APD on the skin surface exposed to half-wave dipole radiation at 10, 30, and 90 GHz considered

<figure><img src="image_7.png" /><figcaption>**FIGURE 1.** Schematic illustration of the dominant factors influencing variability in SAR and temperature rise.</figcaption></figure>

a three-layer tissue model with the skin, fat, and muscle being represented by random permittivities and conductivities [172]. The results showed that uncertainties in the inner layers had only minor effects, indicating that stochastic APD assessment can be reliably performed using simplified 2D models.

In [173], the importance of accounting for antenna/body interactions in APD evaluation was demonstrated.

## VIII. SUMMARY

This review highlights the mechanism by which variability across anatomical, thermophysiological, and numerical human models affects the prediction of temperature rise in computational dosimetry. Computational dosimetry plays a crucial role in defining the physical quantities used in the guidelines and setting the limit. The conceptual framework is schematically illustrated in Fig. 1, highlighting that SAR variability is largely driven by anatomical scaling, whereas temperature rise is predominantly governed by thermophysiological parameters. To complement this, the key quantitative findings are summarized in Table 2.

Model variability and computational uncertainty in SAR showed consistent patterns across studies. For psSAR<sub>10g</sub> under local exposure, children and adults exhibit broadly similar values, although anatomical factors, such as head size, can yield higher localized absorption in children. Intermodel analyses indicated variability on the order of ~30%, with rare extreme cases up to a threefold difference. For WBASAR, smaller and child models generally show 40%–60% higher values than adults, whereas additional variability arises from body shape, modeling method, and tissue properties (10%–30%), with polarization and incidence angle occasionally producing variations of up to ~60%. Computational uncertainty, which arises from discretization, boundary conditions, and algorithmic implementation, is typically small; however, additional errors of ±10%–20% may occur if the parameters are not properly controlled.

The model variability in the temperature rise showed a different pattern compared with the SAR. For the brain and eye, heating factors per psSAR<sub>10g</sub> remained consistently below ~0.12–0.19 °C·kg/W, corresponding to <0.1 °C–0.2 °C
<figure><img src="image_8.png" /></figure>

rises under guideline limits, with limited differences between adults and children. In the skin, variability is mainly due to tissue thickness and microstructure, generally accounting for 10%-20%, whereas pulse exposures highlight the importance of transient surface heating. Core temperature rise is smaller in children and higher in fetuses and the elderly; however, in occupational scenarios, environmental and clothing factors outweigh EMF-induced heating. Furthermore, vascular models, which explicitly represent major blood vessels, have demonstrated additional influence on local temperature distributions, particularly near large arteries and in deep brain regions, although their contribution is generally secondary compared to bulk blood perfusion [174], [175].

Overall, unlike SAR, where anatomical scaling and body size are the dominant sources of variability, temperature rise is more sensitive to thermal and physiological parameters, such as blood perfusion and thermoregulatory responses. While further investigations into these aspects are warranted, with several challenges already identified by international standardization bodies [10], [176], the variability observed to date remains within the margins covered by the reduction factors in ICNIRP and IEEE guidelines, supporting both the robustness of current limits and their value for future refinement. Further research is essential, particularly in view of emerging applications such as 6G.

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AKIMASA HIRATA (Fellow, IEEE) received the B.E. and M.E. degrees in communications engineering from Osaka University, Suita, Japan, in 1996, 1998, and 2000, respectively.

From 1999 to 2001, he was a Research Fellow of the Japan Society for the Promotion of Science. In 2001, he joined the Department of Communications Engineering, Osaka University, as an Assistant Professor. In 2004, he joined the Department of Computer Science and Engineering, Nagoya Institute of Technology as an Associate Professor, where he is currently a Full Professor and Research Director. His research interests include electromagnetic field protection, risk management system for heat-related illness, methods in neuroscience, antennas, filters, and related computational techniques.

Prof. Hirata is the Chair (2024 to 2028) and Main Commissioner (2016 to 2028) of International Commission on Non-Ionizing Radiation Protection (ICNIRP), an Associate Editor for IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, an Executive Editorial Board Member of physics in medicine and biology, and a member of administrative committee and a Subcommittee (EMF Dosimetry Modeling) Chair of IEEE International Committee on Electromagnetic Safety. He was the recipient of several awards including Young scientists' Prize in 2006 and Prizes for Science and Technology (Research Category in 2011; Public Understanding Promotion Category in 2014 and 2020; Development Category in 2024) by the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology, Japan, and IEEE EMC-S Technical Achievement Award in 2015, the Japan Academy Medal and JSPS Prize in 2018, Japan Open Innovation Prize (President of the Science Council of Japan Prize in 2022) from the Cabinet Office. IEEE EMC-S Richard R. Stoddart Award for Outstanding Performance in 2023, and EMC-S Motohisa Kanda Award in 2025. He is a fellow of Institute of Physics, IEICE, IEE Japan, and Asia Pacific AI Association, and a member of Bioelectromagnetics Society.
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**ILKKA LAAKSO** (Member, IEEE) received the M.Sc. degree in electromagnetics and circuit theory from Helsinki University of Technology, Espoo, Finland, in 2007, and the D.Sc. (Tech.) degree in electromagnetics from Aalto University, Espoo, in 2011.

From 2011 to 2015, he was with the Nagoya Institute of Technology, Nagoya, Japan, as a Postdoctoral Researcher, Research Assistant Professor, and Research Associate Professor. Since 2015, he has been leading the research group of electromagnetics in health technologies with Aalto University, where he is currently an Associate Professor. He is currently a member of the Task Group on Radiofrequency Fields and Health of the World Health Organization, Main Commissioner of the International Commission of Non-Ionizing Radiation Protection, and an Official Member (Finland) of the Commission K “Electromagnetics in Biology and Medicine” of the International Union of Radio Science. He was the recipient of the IEEE Electromagnetic Compatibility Society Technical Achievement Award for contribution to computational dosimetry of human exposure to electromagnetic fields from low frequency to millimeter waves.

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**YOSHIKI KUBOTA** received the Ph.D. degree in Intelligence Science from the Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 2009.

In 2009, he joined the National Institute of Radiological Sciences, Chiba, Japan. In 2012, he joined Gunma University Heavy Ion Medical Center, Maebashi, Japan, as an Assistant Professor and Medical Physicist. In 2021, he joined B dot Medical Inc., Tokyo, Japan. Since 2024, he has been an Associate Professor (specially appointed) with the Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Japan. His research interests include medical image processing, medical physics, and machine learning-based conductivity estimation for applications in electric field simulations.

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**FRANCESCA APOLLONIO** (Member, IEEE) received the Ph.D. degree from the Sapienza University of Rome, Rome, Italy, in 1998.

She has been a Full Professor with the Department of Electronic Engineering, Sapienza University of Rome, where she has been affiliated since 2003. She is the Chair of URSI Commission K, Electromagnetics in Biology and Medicine, and is a member of the Board of Directors of the BioEM Society. Within the BioEM Society, she was the Technical Program Committee Chair for the 2024–2025 annual meeting (BioEM2025). She has authored more than 200 scientific publications on peer-reviewed international journals and conferences and chapter books. Her research interests focus on the interaction between electromagnetic fields and biological systems, including electroporation, smart drug delivery, molecular simulations of complex systems and the dosimetry and design of exposure systems. Since 2022, she has been a member of the IEEE MTT-S Technical Committee TC-28, and since 2020 she has been part of the Scientific Expert Group of the International Commission on Non-Ionizing Radiation Protection. From 2016 to 2020, she was the National Representative for COST Action CA15211. She was also the Technical Program Committee Chair for the BioEM2016 Annual Meeting of the Bioelectromagnetics Society and the European BioElectromagnetics Association. From 2012 to 2015, she was a member of the BEMS Board of Directors.

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**JUNQING LAN** was born in Datong, China, in 1983. He received the Ph.D. degree in radio physics from Sichuan University, Chengdu, China, in 2013.

From 2019 to 2021, he was a Visiting Scholar and Specially Appointed Researchers with the Nagoya Institute of Technology, Nagoya, Japan. In 2022, he was the Associate Professor with the Chengdu University of Information Technology, Chengdu. Since 2014, he has been an Assistant Professor with the Chengdu University of Information Technology, Chengdu, China. His current research interests include electromagnetic dosimetry modelling, wireless power transmission, and biological electromagnetic effects.

Prof. Lan is currently a member of IEEE ICES Technical Committee 95.

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**SACHIKO KODERA** (Member, IEEE) received the B.E. and M.E. degrees in electrical and computer engineering and the Ph.D. degree in computer science from the Nagoya Institute of Technology, Nagoya, Japan, in 2002, 2006, and 2019, respectively. In 2016, she joined the Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, where she is currently an Associate Professor. Her current research interests include electromagnetic and thermal dosimetry modeling in humans for radio frequency and am-

bient heat exposures.

Dr. Kodera is a member of the Subcommittee six in Technical Committee 95 of IEEE International Committee on Electromagnetic Safety and a member of the Scientific Expert Group of International Commission on Non-Ionizing Radiation Protection. She was the recipient of the Prizes for Science and Technology (Public Understanding Promotion Category, in 2020) from the Commendation for Science and Technology, Minister of Education, Culture, Sports, Science, and Technology, Japan, and Japan Open Innovation Prize (President of the Science Council of Japan Prize, in 2022) from the Cabinet Office.

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**KUN LI** (Member, IEEE) received the B.E. degree in communication engineering from the Nanjing University of Posts and Telecommunications, Nanjing, China, in 2011, and the Ph.D. degree in electrical engineering from the University of Toyama, Toyama, Japan, in 2017.

From 2017 to 2019, he was a Researcher with the National Institute of Information and Communications Technology, Tokyo, Japan. From 2020 to 2023, he was an Assistant Professor with Kagawa University, Takamatsu, Japan. He was also a Visiting Researcher with CNRS/IETR, University of Rennes 1, Rennes, France, from 2022 to 2023. In 2023, he joined Advanced Wireless and Communication Research Center, The University of Electro-Communications, Tokyo, Japan, where he is currently an Associate Professor. His research interests include over-the-air testing, MIMO, body area networks, and RF-EMF exposure.

Dr. Li was the recipient of the Outstanding Associate Editor Award from IEEE Antenna and Wireless Propagation Letters in 2025, where he was an Associate Editor. He was also the recipient of the URSI Young Scientist Award in 2020. He is currently the Early Career Representative of URSI Commission K and the Co-Chair of a Working Group under Subcommittee 6, the IEEE International Committee on Electromagnetic Safety TC-95. He is a senior member of URSI and a member of IEICE.
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**MICAELA LIBERTI** (Member, IEEE) received the M.Sc. degree in electronic engineering and the Ph.D. degree from the Sapienza University of Rome, Rome, Italy, in 1995 and 2000, respectively. She is currently an Associate Professor with the Department of Information Engineering, Electronics, and Telecommunications, Sapienza University of Rome. Her research interests include theoretical modeling in bioelectromagnetics, biomedical applications of electromagnetic fields, microdosimetry, and exposure system design.

She was the national substitute representative for COST Action TD1104 on electroporation-based technologies from 2012 to 2015 and Co-Chair of BioEM 2019 in Montpellier, France. She was the President of the European Bioelectromagnetics Association, from 2020 to 2021. Since 2021, she has been a member of the Scientific Expert Group of the International Commission on Non-Ionizing Radiation Protection and Technical Advisory Committee of URSI Commission K. Since 2022, she has been a member of TC28 of the IEEE MTT Society. She is currently the President-Elect of the BioEM Society.

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**DRAGAN POLJAK** (Senior Member, IEEE) received the Ph.D. degree in electrical engineering from the University of Split, Split, Croatia, in 1996. He is currently the Full Professor with the Department of Electron. and Computing, University of Split. His research interests include oriented to computational electromagnetics (electromagn. compatibility, bioelectromagnetics and plasma physics). He has authored or coauthored more than 160 journals and 250 conference papers, and authored some books, such as two by Wiley,

one by IEEE and one by Elsevier. He is a member of Editorial Board of Eng. Anal. with Boundary Elements, Math. Problems in Eng. and IET Sci. Measur. & Techn. He was awarded by several prizes for his achievements, such as National Prize for Science in 2004 and 2023, Croatian section of IEEE annual Award in 2016, Technical Achievement Award of the IEEE EMC Society in 2019 and George Green Medal from University of Mississippi in 2021. From 2013 to 2021, Prof. Poljak was a member of the board of the Croatian Science Foundation. He is currently involved in ITER physics and DONES EUROfusion collab. and in Croatian center for excellence in research for tech. sciences. He is active in few working groups of the IEEE/International Committee on Electromagnetic Safety (ICES) Technical Committee 95 SC6 EMF Dosimetry Modeling.

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**KENSUKE SASAKI** (Member, IEEE) received the B.E., M.E., and Ph.D. degrees in electrical and electronic engineering from Tokyo Metropolitan University, Tokyo, Japan, in 2006, 2008, and 2011, respectively.

He is currently a Planning Manager with the Strategic Planning Office, National Institute of Information and Communications Technology, Japan. He is also a Visiting Associate Professor with the Nagoya Institute of Technology, Japan, since 2022.

His research interests include electromagnetic theory, bioelectromagnetics, and dielectric properties measurement.

Dr. Sasaki is a member of Scientific Expert Group of International Commission on Non-Ionizing Radiation Protection, from 2018 to 2020 and since 2024. He was the Early Carrier Representative of Commission K, the International Scientific Radio Union, from 2017 to 2023. He is also the Co-Chair of Working Group 6 under Subcommittee 6, the IEEE International Committee on Electromagnetic Safety TC-95, since 2022. He was the recipient of the 2009 Young Scientist Award of the URSI, 2012 Best Paper Award of the IEEJ, 2020 Achievement Award of the IEICE, and IEEE EMC-S Motohisa Kanda Award in 2025.

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**MAXIME ZHADOBOV** (Senior Member, IEEE) received the Ph.D. and Habilitation à Diriger des Recherches degrees from the Institut d'Electronique et des Technologies du numerique (IETR), University of Rennes, Rennes, France, in 2006 and 2016, respectively. He was a Postdoctoral Researcher with the Center for Biomedical Physics, Temple University, Philadelphia, PA, USA, until 2008, and then joined the French National Center for Scientific Research (CNRS). He is currently Senior Research Scientist with the

IETR/CNRS. From 2017 to 2024, he was in charge of the Electromagnetic Waves in Complex Media (eWAVES) research team and a member of the Scientific Council of the IETR. He has coauthored five book chapters, more than 100 research papers in peer-reviewed international journals, and more than 200 contributions to conferences and workshops. His research interests include innovative biomedical applications of electromagnetic fields and associated technologies. He has also been a member of Board of Directors of International BioEM society, since 2024 and was an elected member of EBEA Council from 2017 to 2021. He is also a member of IEEE TC95.4 and the President of URSI France Commission K till 2025. His review article in the *International Journal of Microwave and Wireless Technologies* was the most cited paper during 2016–2025. A paper published by his research group in 2019 is in journal Top 100 of Nature Scientific Reports. He is an Associate Editor for IEEE JOURNAL OF ELECTROMAGNETICS, RF AND MICROWAVES IN MEDICINE AND BIOLOGY and was the Guest Editor of several special issues, including Human Exposure in 5G and 6G Scenarios of Applied Sciences and Advanced Electromagnetic Biosensors for Medical, Environmental and Industrial Applications of Sensors.

He has been involved in 31 research projects (16 as PI). He was a TPC member and/or Session Organizer with international conferences, including IEEE AP-S/URSI 2024, URSI AT-RASC 2024, AES 2023, BioEM 2023, EUMW2022, IEEE IMBioC 2022, AT-AP-RASC 2022, BioEM 2019, EuMW 2019, IEEE iWEM 2017, MobiHealth 2015–2017, BodyNets 2016, and IMWS-Bio 2014. He was the TPC Co-Chair of BioEM 2021/2020 and LOC member of BioEM 2025. He was also on review boards of more than 15 international journals and conferences, and has been acting as an expert at research councils worldwide. He was the recipient of Research and Innovation Award of Grand Ouest Foundation in 2022, CNRS Medal in 2018, EBEA Award for Excellence in Bioelectromagnetics in 2015, and Brittany’s Young Scientist Award in 2010. Since 2010, the Ph.D. students he worked with was the recipient of eight national scientific awards and six awards from the Bioelectromagnetics Society, URSI, IEEE Antennas and Propagation and IEEE Microwave Theory and Technology Societies.

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**YINLIANG DIAO** (Member, IEEE) received the B.E. degree from Chongqing University, Chongqing, China, in 2008, the M.S. degree in electronic engineering from the Beijing University of Posts and Telecommunications, Beijing, China, in 2011, and the Ph.D. degree in electronic engineering from the City University of Hong Kong, Hong Kong, in 2016.

Since 2017, he has been with the College of Electronic Engineering, South China Agricultural University, Guangzhou, China, initially as an As-

sistant Professor and currently as an Associate Professor. In 2019, he also joined the Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Japan, where he is currently a Guest Associate Professor. His research interests include electromagnetic dosimetry modeling and electromagnetic compatibility.

Dr. Diao is a Co-Chair of Subcommittee 6 of IEEE International Committee on Electromagnetic Safety TC-95, and a member of the Scientific Expert Group of International Commission on Non-Ionizing Radiation Protection. He was a recipient of the Young Scientist Award from URSI GASS 2020 and EMC-S Motohisa Kanda Award in 2025.