gms | German Medical Science

58. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e. V. (DGNC)

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

26. bis 29.04.2007, Leipzig

Finite element modeling of neuroelectronic interfaces as development tool for neuroprostheses

Finite Elemente-Modellierung neuroelektronischer Schnittstellen als Werkzeug zur Optimierung von Neuroprothesen

Meeting Abstract

Suche in Medline nach

  • corresponding author J. Kaminsky - Allgemeine Neurochirurgie, Neurozentrum, Universitätsklinikum Freiburg
  • G. Brand - Regionales Computerzentrum, Universität Hannover

Deutsche Gesellschaft für Neurochirurgie. 58. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e.V. (DGNC). Leipzig, 26.-29.04.2007. Düsseldorf: German Medical Science GMS Publishing House; 2007. DocP 014

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/meetings/dgnc2007/07dgnc269.shtml

Veröffentlicht: 11. April 2007

© 2007 Kaminsky et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Objective: Neuroprosthetics is a promising modern field of restorative surgery. The functional recovery of hearing and visual functions as well as the voluntary control of artificial limbs are currently focussed applications. Due to miniaturisation and high performance computer systems limitations by signal processing became less important. The bottleneck according to signal transmission is caused by the interface between electronic and nervous system. The signal transmission is limited by the number and conductive properties of the used surface or penetrating electrodes. Over time scaring and chronic damage of the nervous tissue compromise the interface. Our aim was to develop an environment for simulating and testing different influencing variables beginning with the biomechanical aspects.

Methods: Based on MR images (3D-MPR, T2w) of a brainstem a 3D-finite element (FE) model was generated with automated routines developed in a prior research project. The brain tissue material properties were assigned corresponding to the MRI-intensity values and data of the literature. Different geometrically designed penetrating and surface electrodes were integrated into the model simulating auditory brain stem implants. Parameter studies were performed with varying material properties of the electrodes. Simulated stress and strain values were evaluated.

Results: The material properties of the generated FE-model are nonlinear implemented for the brain tissue. Surface- and penetrating electrodes with varying material properties were successfully integrated and tested. High tissue stresses were detected at the tip of penetrating electrodes with straight pin-design. These stress-peaks could be reduced both, by electrodes with clubbed tips and discontinuous material properties along the pin-axis. Surface electrodes with small diameter showed minimal stress values.

Conclusions: The developed FE-environment was successfully tested to evaluate stress-distributions for different geometric and material properties of brain stem electrodes. Further developments of this software may help to optimise neuroelectronic interfaces. New Electrode-designs and applications can be tested and preselected to avoid unnecessary experimental in vivo studies, not only contributing to a cost reduction. New software applications for the evaluation of electric and thermal effects at the neuroelectronic interface are in the development stage and offer promising new application fields.