• DocumentCode
    35635
  • Title

    The Forward Problem of Electroarthrography: Modeling Load-Induced Electrical Potentials at the Surface of the Knee

  • Author

    Qingyi Han ; Buschmann, Michael D. ; Savard, Pierre

  • Author_Institution
    Inst. de genie Biomed., Ecole Polytech. de Montreal, Montreal, QC, Canada
  • Volume
    61
  • Issue
    7
  • fYear
    2014
  • fDate
    Jul-14
  • Firstpage
    2020
  • Lastpage
    2027
  • Abstract
    Electroarthrography (EAG) is a novel technology recently proposed to detect cartilage degradation. EAG consists of recording electrical potentials on the knee surface while the joint is undergoing compressive loading. Previous results show that these signals originating from streaming potentials in the cartilage reflect joint cartilage health. The aim of this study is to contribute to the understanding of the generation of the EAG signals and to the development of interpretation criteria using computer models of the human knee. The knee is modeled as a volume conductor composed of different regions characterized by specific electrical conductivities. The source of the EAG signal is the load-induced interstitial fluid flow that transports ions within the compressed cartilage. It is modeled as an impressed current density in different sections of the articular cartilage. The finite-element method is used to compute the potential distribution in two knee models with a realistic geometry. The simulated potential distributions correlate very well with previously measured potential values, which further supports the hypothesis that the EAG signals originate from compressed cartilage. Also, different localized cartilage defects simulated as a reduced impressed current density produce specific potential distributions that may be used to detect and localize cartilage degradation. In conclusion, given the structural and electrophysiological complexity of the knee, computer modeling constitutes an important tool to improve our understanding of the generation of EAG signals and of the various factors that affect the EAG signals so as to help develop the EAG technology as a useful clinical tool.
  • Keywords
    bioelectric potentials; biological tissues; biomechanics; biotransport; compressibility; current density; diseases; finite element analysis; flow simulation; medical signal processing; surface conductivity; surface potential; EAG signal generation; articular cartilage; cartilage degradation detection; compressed cartilage; compressive loading; computer models; electrical potential recording; electroarthrography; electrophysiological complexity; finite-element method; forward problem; human knee; interpretation criteria development; ion transports; joint cartilage health; knee surface; load-induced electrical potential modeling; load-induced interstitial fluid flow; localized cartilage defects; potential distribution; realistic geometry; reduced impressed current density; simulated potential distributions; specific electrical conductivities; specific potential distributions; structural complexity; volume conductor; Computational modeling; Current density; Electric potential; Electrodes; Geometry; Joints; Solid modeling; Arthritis; bioelectric phenomena; finite-element analysis; medical simulation;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2014.2312104
  • Filename
    6767073