• DocumentCode
    2963398
  • Title

    High resolution boundary element forward models for sensor arrays: an application to electroencephalography

  • Author

    Loftus, Caitlinn ; Jenkinson, Mark ; Egan, Gary F.

  • Author_Institution
    Howard Florey Inst., Melbourne Univ., Vic., Australia
  • fYear
    2004
  • fDate
    14-17 Dec. 2004
  • Firstpage
    599
  • Lastpage
    604
  • Abstract
    The forward problem of electroencephalography (EEG) involves mapping current sources in the brain to voltages at sensors (electrodes) on the scalp. Boundary element modeling is a numerical method which has been widely applied to this problem. Here, the boundary element approach is validated for spherical models for which analytic solutions can be calculated. Three aspects of the basic approach were varied: the type of potential approximation (de Munck, J.C., IEEE Trans. Biomed. Eng., vol.39, no.9, p.986-90, 1992); the use of a solid angle correction (Heller, L., Digital Image Synthesis and Inverse Optics, Proc. SPIE, vol.1351, p.376-90, 1990); the isolated skull correction (Hamalainen, M.S. and Sarvas, J., IEEE Trans. Biomed. Eng., vol.36, no.2, p.165-71, 1989). The effects of locally non-uniform meshes were also considered. The calculations were performed using six different mesh resolutions, including mesh resolutions significantly higher than those previously used for forward model evaluation.
  • Keywords
    approximation theory; array signal processing; boundary-elements methods; electroencephalography; medical signal processing; EEG; electroencephalography; forward problem; high resolution boundary element forward models; isolated skull correction; nonuniform meshes; potential approximation; sensor arrays; solid angle correction; spherical models; Biomedical optical imaging; Brain modeling; Digital images; Electrodes; Electroencephalography; Numerical models; Scalp; Sensor arrays; Solids; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
  • Print_ISBN
    0-7803-8894-1
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2004.1417529
  • Filename
    1417529