Intercomparison of the averaged induced electric field in learning-based human head models exposed to low-frequency magnetic fields

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorDiao, Yinliangen_US
dc.contributor.authorRashed, Essam A.en_US
dc.contributor.authorGiaccone, Lucaen_US
dc.contributor.authorLaakso, Ilkkaen_US
dc.contributor.authorLi, Congshengen_US
dc.contributor.authorScorretti, Riccardoen_US
dc.contributor.authorSekiba, Yoichien_US
dc.contributor.authorYamazaki, Kenichien_US
dc.contributor.authorHirata, Akimasaen_US
dc.contributor.departmentDepartment of Electrical Engineering and Automationen
dc.contributor.groupauthorElectromagnetics in Health Technologyen
dc.contributor.organizationSouth China Agricultural Universityen_US
dc.contributor.organizationUniversity of Hyogoen_US
dc.contributor.organizationPolytechnic University of Turinen_US
dc.contributor.organizationChina Academy of Information and Communications Technologyen_US
dc.contributor.organizationInstitut national des sciences appliquées de Lyonen_US
dc.contributor.organizationDenryoku Computing Center Ltden_US
dc.contributor.organizationCentral Research Institute of Electric Power Industryen_US
dc.contributor.organizationNagoya Institute of Technologyen_US
dc.date.accessioned2023-05-10T06:29:24Z
dc.date.available2023-05-10T06:29:24Z
dc.date.issued2023en_US
dc.descriptionPublisher Copyright: Author
dc.description.abstractAnatomical human models have been widely used in the assessment of induced field strength for low-frequency (LF) electromagnetic field exposure. One bottleneck is the assignment of a single electrical conductivity to all the voxels of the corresponding tissue. This simplification is known to cause computational artifact; therefore, a large reduction factor was considered in international guidelines and standards. Recently, head models with nonuniform conductivities generated using deep learning networks were proposed, and the effect on the reduction of staircasing artifacts was demonstrated. If the effectiveness of the models is confirmed for different models and codes, it would be useful to derive the relationship between the internal and external field strengths needed for setting the exposure limit. The Subcommittee 6 of the IEEE International Committee on Electromagnetic Safety Technical Committee 95 launched a working group to conduct the first intercomparison study of the induced electric field in learning-based head models exposed to LF magnetic fields. Seven international research groups have cooperated in this joint study. The highest relative difference (RD) in averaged electric fields was 23%, which is attributable to the difference caused the by scalar potential finite difference (SPFD) method and finite element method. Except for one group, the RDs in the 100th and 99th percentile values of the averaged electric field using the SPFD method with different solvers and codes were below 1%, indicating that the uncertainty due to different codes is sufficiently small under the same exposure scenarios. The findings would be informative for future revision of exposure limits and reduction factors in the exposure standard, which is closely related to computational uncertainty.en
dc.description.versionPeer revieweden
dc.format.extent14
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationDiao, Y, Rashed, E A, Giaccone, L, Laakso, I, Li, C, Scorretti, R, Sekiba, Y, Yamazaki, K & Hirata, A 2023, ' Intercomparison of the averaged induced electric field in learning-based human head models exposed to low-frequency magnetic fields ', IEEE Access, vol. 11, pp. 38739-38752 . https://doi.org/10.1109/ACCESS.2023.3268133en
dc.identifier.doi10.1109/ACCESS.2023.3268133en_US
dc.identifier.issn2169-3536
dc.identifier.otherPURE UUID: 1c482fce-b0b1-4f55-94f7-d4c06a520481en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/1c482fce-b0b1-4f55-94f7-d4c06a520481en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85153535105&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/107898284/Intercomparison_of_the_Averaged_Induced_Electric_Field_in_Learning_Based_Human_Head_Models_Exposed_to_Low_Frequency_Magnetic_Fields.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/120704
dc.identifier.urnURN:NBN:fi:aalto-202305103042
dc.language.isoenen
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Accessen
dc.relation.ispartofseriesVolume 11en
dc.rightsopenAccessen
dc.subject.keywordComputational modelingen_US
dc.subject.keywordConductivityen_US
dc.subject.keywordElectric fieldsen_US
dc.subject.keywordelectromagnetic safetyen_US
dc.subject.keywordElectromagneticsen_US
dc.subject.keywordHuman factorsen_US
dc.subject.keywordhuman protectionen_US
dc.subject.keywordLow frequencyen_US
dc.subject.keywordMagnetic fieldsen_US
dc.subject.keywordMagnetic headsen_US
dc.subject.keywordSafetyen_US
dc.subject.keywordstandardizationen_US
dc.titleIntercomparison of the averaged induced electric field in learning-based human head models exposed to low-frequency magnetic fieldsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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