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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: 2024-08-28Bibliographically approved
In thesis
1. Fully Integrated Bioimpedance Spectroscopy Interface for Wearable Electrical Impedance Myography
Open this publication in new window or tab >>Fully Integrated Bioimpedance Spectroscopy Interface for Wearable Electrical Impedance Myography
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Multi-Frequency surface Electrical Impedance Myography (MF-sEIM) is a technique that provides valuable electrophysiological information of muscles. This technique measures bio-Z spectroscopy of muscles, and applies Ohm's law by injecting a small-amplitude and high-frequency current into tissues and measuring the voltage response. As biological tissues are electrolytic conductors, this technique provides information on fundamental dielectric properties of tissues, which are an objective biomarker of neuromuscular disorders and have practical value in several muscle healthcare applications. Due to its versatility, simplicity, and ease of integration, this technique is a great candidate to complement stand-alone surface electromyography (sEMG) in wearable devices for continuous monitoring of muscle health. Nonetheless, wearable MF-sEIM imposes challenging requirements on the bio-Z spectroscopy interface. Previously reported solutions fall short of meeting these requirements, or do so with low power efficiency.

This thesis focuses on the research and development of a fully integrated bio-Z spectroscopy interface, which complies with the challenging requirements of wearable MF-sEIM in a power-efficient way. The electrophysiological mechanisms of MF-sEIM and the system-level requirements for clinical relevance were investigated, as MF-sEIM is a relatively novel technique, which requires standarization. From this established set of requirements, the main building blocks of the \mbox{bio-Z} spectroscopy interface, i.e., the current signal generator (CSG), and voltage readout, were developed. The CSG generates pseudo-sine waves through direct digital synthesis (DDS) to obtain the required linearity with high power efficiency. A high-linearity full current-mode CSG was also proposed to comply with the stricter bio-Z accuracy requirements of clinical diagnostics. The voltage readout is based on a low-IF quadrature (I/Q) demodulation architecture and features a pseudo 2-path bandpass (BP) Delta-Sigma ADC to achieve high precision and power-to-noise efficiency. A mixer-first analog front-end (AFE) was also proposed to enable bio-Z spectroscopy measurements employing dry electrodes. The bio-Z interface was integrated with a 16-Channel sEMG AFE and a 4-Channel neuromuscular stimulator (NMES) in an application-specific integrated circuit (ASIC). Experimental results show that the implemented bio-Z spectroscopy interface achieves a comparable performance with the state of the art, while being capable of detecting the large baseline and the time-varying impedances of muscle. A proof-of-concept system, based on the multi-modal ASIC, was developed. This system demonstrates the potential of combining real-time monitoring of MF-sEIM and sEMG for detecting muscle fatigue, enabling efficient closed-loop NMES.

Abstract [sv]

Multifrekvent ytelektroimpedansmyografi (MF-sEIM) är en teknik som ger värdefull elektrofysiologisk information om muskler. Denna teknik mäter bioimpedans-spektroskopi (bio-Z-spektroskpi) av muskler och tillämpar Ohms lag genom att injicera en högfrekvent småsignalström i vävnader och mäta spänningssvaret. Eftersom biologiska vävnader är elektrolytiska ledare, ger denna teknik information om grundläggande dielektriska egenskaper hos vävnader, som är en objektiv biomarkör för neuromuskulära störningar och har praktiskt värde i flera tillämpningar för muskelsjukvård. På grund av dess mångsidighet och enkel integration är denna teknik en utmärkt kandidat för att komplettera fristående ytelektromyografi (sEMG) i bärbara enheter för kontinuerlig övervakning av muskelhälsa. Icke desto mindre ställer bärbar MF-sEIM utmanande krav på bio-Z-spektroskopigränssnittet. Tidigare rapporterade lösningar uppfyller inte dessa krav, eller gör det med låg energieffektivitet.

Denna avhandling fokuserar på forskning och utveckling av ett helt integrerat bio-Z-spektroskopigränssnitt, som uppfyller de utmanande kraven för bärbar MF-sEIM på ett energieffektivt sätt. De elektrofysiologiska mekanismerna för MF-sEIM och kraven på systemnivå för klinisk relevans undersöktes, eftersom MF-sEIM är en relativt ny teknik som kräver standardisering. Från de definerade kraven på systemnivå utvecklades huvudbyggstenarna för bio-Z-spektroskopigränssnittet, dvs. strömsignalgeneratorn (CSG) och spänningsavläsningen. CSG genererar pseudo-sinusvågor genom direkt digital syntes (DDS) för att erhålla den erforderliga linjäriteten med hög energieffektivitet. En CSG i fullströmsläge med hög linjäritet föreslogs också för att uppfylla de striktare noggrannhetskraven på bioimpedansmätning för klinisk diagnostik. Spänningsavläsningen är baserad på en demoduleringsarkitektur med låg IF-kvadratur (I/Q) och har en pseudo 2-vägs bandpass (BP) Delta-Sigma ADC för att uppnå hög precision och energi till brus effektivitet. En mixer-framför analog front-end (AFE) föreslogs också för att möjliggöra bio-Z-spektroskopimätningar med användning av torra elektroder. Bio-Z-gränssnittet integrerades med en 16-kanals sEMG AFE och en 4-kanals neuromuskulär stimulator (NMES) i en applikationsspecifik integrerad krets (ASIC). Experimentella resultat visar att det implementerade bio-Z-spektroskopigränssnittet uppnår en prestanda som är jämförbar med den senaste tekniken, samtidigt som den kan detektera storsignalsimpedansen hos muskler och dess tidsvariation. Ett prototyp, baserat på den multimodala ASIC, utvecklades. Detta system visar potentialen i att kombinera realtidsövervakning av MF-sEIM och sEMG för att upptäcka muskeltrötthet, vilket möjliggör effektiva NMES med återkoppling.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2024. p. xix, 84
Series
TRITA-EECS-AVL ; 2024:62
Keywords
Musculoskeletal health, bioimpedance (bio-Z) spectroscopy, electrical impedance myography (EIM), biomedical modeling, ASIC, ultra-low power, high-precision, sinusoidal signal generator, readout, analog front-end, bandpass delta-sigma ADC, multi-modal sensing., Muskuloskeletal hälsa, bioimpedans-spectroscopi (bio-Z-spektroskpi), elektroimpedansmyografi (EIM), biomedicinsk modellering, ASIC, ultralåg energi, hög precision, sinusformad signalgenerator, avläsning, analog front-end, bandpass delta-sigma ADC, multimodal avkänning.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Information and Communication Technology
Identifiers
urn:nbn:se:kth:diva-352340 (URN)978-91-8106-022-5 (ISBN)
Public defence
2024-09-27, https://kth-se.zoom.us/j/2593490856, Ka-Sal C, Electrum, Kistagången 16, Kista, 13:00 (English)
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research, ITM17-0079
Note

QC 20240829

Available from: 2024-08-29 Created: 2024-08-28 Last updated: 2024-08-29Bibliographically approved

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Fernández Schrunder, AlejandroRodriguez, SaulRusu, Ana

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