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Estimating Human Fat and Muscle Conductivity From 100 Hz to 1 MHz Using Measurements and Modelling
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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13
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Bioelectromagnetics, Volume 46, issue 1
Abstract
The electrical conductivity of human tissues is a major source of uncertainty when modelling the interactions between electromagnetic fields and the human body. The aim of this study is to estimate human tissue conductivities in vivo over the low-frequency range, from 30 Hz to 1 MHz. Noninvasive impedance measurements, medical imaging, and 3D surface scanning were performed on the forearms of ten volunteer test subjects. This data set was used to create subject-specific forearm models, numerically solve an electrostatic forward problem, after which the tissue conductivities could be estimated by solving a probabilistic inverse problem. The electrical conductivity of skeletal muscle was found to be highly anisotropic at frequencies below 10 kHz, with conductivities of 0.13 (95% credible interval (CrI): 0.10–0.16) S/m perpendicular and 0.56 (CrI: 0.52–0.60) S/m parallel to the muscle fibre direction. This anisotropy decreased with increasing frequency with these values being 0.65 (CrI: 0.48–1.00) S/m and 0.78 (CrI: 0.72–0.85) S/m at 1 MHz. The conductivity of subcutaneous fat was found to be almost constant across the considered frequency range, with values of 0.21 (CrI: 0.12–0.31) S/m and 0.22 (CrI: 0.07–0.37) S/m at 10 kHz and 1 MHz, respectively. Our study provides robust uncertainty bounds for human tissue conductivity values, which are crucial in the computational assessment of human electromagnetic field exposure. Additionally, our findings are applicable to other fields of modelling such as medical stimulation or measurement technologies.
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Publisher Copyright: © 2025 The Author(s). Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.
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Kangasmaa, O, Laakso, I & Schmid, G 2025, 'Estimating Human Fat and Muscle Conductivity From 100 Hz to 1 MHz Using Measurements and Modelling', Bioelectromagnetics, vol. 46, no. 1, e22541. https://doi.org/10.1002/bem.22541