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An integrated experimental-computational electromagnetic-thermal framework for predicting bioheat response of the
Ivan Dominik Horvat1, Klementina Vidjak2, Jana Wedel3
1Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, Maribor, 2000, Slovenia.
Abstract:
The increasing use of wearable wireless devices operating in close proximity to the human body has raised the need for reliable assessment of electromagnetic exposure and associated thermal effects in biological tissue. In particular, wireless earbuds produce both electromagnetic energy absorption and device self-heating as potential sources of localized temperature elevation near the head. This study presents an integrated experimental-computational-electromagnetic-thermal framework for predicting the bioheat response of the human head. The approach combines infrared thermography measurements on a tissue-mimicking ear phantom with inverse heat-transfer analysis to estimate effective thermal parameters and device-related heat generation. These parameters are incorporated into a 3D bioheat model of an anatomically realistic head. Electromagnetic field distributions are obtained from full-wave simulations of a representative earbud antenna initially designed for the 2.45 GHz ISM band and evaluated at its tissue-loaded resonance near 2.3 GHz, and the resulting spatially resolved pointwise specific absorption rate (SAR) is applied as a volumetric heat source in the thermal model. The coupled problem is solved using a custom OpenFOAM-based bioheat solver. Results show that SAR distributions are highly localized near the ear, whereas the resulting temperature field is smoother due to thermal diffusion. The predicted temperature increase remains confined to the vicinity of the earbud and is relatively small. Device self-heating is identified as the dominant contributor to temperature elevation, while the EM-induced component is comparatively minor. Variations in blood perfusion and tissue thermal conductivity produced only modest changes in the predicted local temperature. The proposed framework provides a consistent and computationally efficient pathway for coupled electromagnetic-thermal analysis, supported by experimental calibration, and is suitable for thermal assessment and design evaluation of wearable wireless devices.

