• DocumentCode
    3684686
  • Title

    Iterative electrodes increase neural recruitment for deep brain stimulation

  • Author

    Xuefeng F. Wei;Naina Iyengar;Andrew H. DeMaria

  • Author_Institution
    The College of New Jersey, Ewing, 08618 USA
  • fYear
    2015
  • Firstpage
    3419
  • Lastpage
    3422
  • Abstract
    Deep brain stimulators require surgical replacement when primary cell batteries are depleted. We designed novel electrode contact geometries based on the principle of iterative element addition as a method of increasing perimeter. Our hypothesis was that these novel, high-perimeter designs would increase surface current density variation and neuronal activation, thus improving stimulation efficiency by decreasing power requirement. Finite element models of iterative electrodes displayed greater surface current density variations on the electrode surface. Subsequent analysis of their activation efficiency when 100 neurons were randomly positioned either parallel or perpendicular to the electrode yielded higher stimulation efficiencies in response to a monophasic cathodic voltage pulse with a pulse width of 100 μs. Recruitment curves showing the percentage of activated axons as a function of stimulation intensity yielded a ~8% and ~24% reduction in threshold voltage and a ~2% and ~28% reduction in power consumption when nerve fibers were oriented parallel and perpendicular to the electrode, respectively. This heightened efficiency would reduce the frequency of surgical replacements of depleted stimulators, as well as induce fewer side effects associate with high voltage requirement for therapeutic stimulation.
  • Keywords
    "Electrodes","Current density","Threshold voltage","Finite element analysis","Brain stimulation"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319127
  • Filename
    7319127