Automatic Detection of Peak Spatial-Average Power Density on Nonplanar Body Models

This paper presents a novel algorithm for the automatic detection of the peak spatial-average power density on nonplanar surfaces of the human body of arbitrary geometry. The algorithm relies only on two input priors as minimal requirements: an unordered set of points on the evaluation surface of interest and the corresponding incident or absorbed power density at each point. To demonstrate its effectiveness, the algorithm is applied to assess the spatially averaged incident power density (IPD) on a realistic model of the human head. Specifically, a computational analysis is conducted considering a theoretical scenario in which the region encompassing the right outer ear is exposed to electromagnetic (EM) energy forming a Gaussian pattern on the corresponding surface. The results are compared to values obtained by using a reference planar evaluation surface prescribed in current international guidelines and standards for limiting human exposure to radio-frequency (RF) EM fields. Overall, the findings support the viability of the proposed algorithm as a reliable solution to assess the exposure of anatomical body models in close proximity to wireless devices operating above 6 GHz, including millimeter wave (MMW) bands anticipated for the fifth generation (5G) technology standard and future advancements.