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A Finite Element Analysis and Circuit Modelling Methodology for Studying Electrical Impedance Myography of Human Limbs
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems. (Mixed-Signals ICs and Systems)ORCID iD: 0000-0001-7549-0858
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems, Integrated devices and circuits.ORCID iD: 0000-0003-0565-9907
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems, Integrated devices and circuits.ORCID iD: 0000-0003-3802-7834
2022 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 69, no 1, p. 244-255Article in journal (Refereed) Published
Abstract [en]

Objective: Electrical impedance myography (EIM) measures bioimpedance over muscles. This paper proposes a circuit-based modelling methodology originated from finite element analysis (FEA), to emulate tissues and effects from anthropometric variations, and electrode placements, on EIM measurements. The proposed methodology is demonstrated on the upper arms and lower legs. Methods: FEA evaluates impedance spectra (Z-parameters), sensitivity, and volume impedance density for variations of subcutaneous fat thickness (tf), muscle thickness (tm), and inter-electrode distance (IED), on limb models over 1Hz-1MHz frequency range. The limbs models are based on simplified anatomical data and dielectric properties from published sources. Contributions of tissues to the total impedance are computed from impedance sensitivity and density. FEA Z-parameters are imported into a circuit design environment, and used to develop a three Cole dispersion circuit-based model. FEA and circuit model simulation results are compared with measurements on ten human subjects. Results: Muscle contributions are maximized at 31.25kHz and 62.5kHz for the upper arm and lower leg, respectively, at 4cm IED. The circuit model emulates variations in tf and tm, and simulates up to 89 times faster than FEA. The circuit model matches subjects measurements with RMS errors < 36.43 and < 17.28, while FEA does with < 36.59 and < 4.36. Conclusions: We demonstrate that FEA is able to estimate the optimal frequencies and electrode placements, and circuit-based modelling can accurately emulate the limbs bioimpedance. Significance: The proposed methodology facilitates studying the impact of biophysical principles on EIM, enabling the development of future EIM acquisition systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 69, no 1, p. 244-255
Keywords [en]
Bioimpedance, Muscle, Electrical Impedance Myography, Finite Element Analysis, Circuit Simulation, Muscles, Electrodes, Integrated circuit modeling, Impedance, Biological system modeling, Dielectrics, Biomedical measurement
National Category
Engineering and Technology Medical and Health Sciences
Research subject
Electrical Engineering; Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-300157DOI: 10.1109/TBME.2021.3091884ISI: 000733943200029PubMedID: 34161236Scopus ID: 2-s2.0-85112454304OAI: oai:DiVA.org:kth-300157DiVA, id: diva2:1588254
Projects
Implantable Bioimpedance
Funder
Swedish Foundation for Strategic Research, ITM17-0079
Note

QC 20230125

Available from: 2021-08-26 Created: 2021-08-26 Last updated: 2023-01-25Bibliographically approved

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Publisher's full textPubMedScopushttps://ieeexplore.ieee.org/document/9463710

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Fernández Schrunder, AlejandroRodriguez, SaulRusu, Ana

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