Medical & Biological Engineering & Computing

, Volume 46, Issue 8, pp 767–777 | Cite as

A hybrid algorithm for solving the EEG inverse problem from spatio-temporal EEG data

  • Guillaume Crevecoeur
  • Hans Hallez
  • Peter Van Hese
  • Yves D’Asseler
  • Luc Dupré
  • Rik Van de Walle
Original Article


Epilepsy is a neurological disorder caused by intense electrical activity in the brain. The electrical activity, which can be modelled through the superposition of several electrical dipoles, can be determined in a non-invasive way by analysing the electro-encephalogram. This source localization requires the solution of an inverse problem. Locally convergent optimization algorithms may be trapped in local solutions and when using global optimization techniques, the computational effort can become expensive. Fast recovery of the electrical sources becomes difficult that way. Therefore, there is a need to solve the inverse problem in an accurate and fast way. This paper performs the localization of multiple dipoles using a global–local hybrid algorithm. Global convergence is guaranteed by using space mapping techniques and independent component analysis in a computationally efficient way. The accuracy is locally obtained by using the Recursively Applied and Projected-MUltiple Signal Classification (RAP-MUSIC) algorithm. When using this hybrid algorithm, a four times faster solution is obtained.


EEG source analysis Space mapping Inverse problems optimization Signal classification 



The authors would like to thank the “Bijzonder Onderzoeksfonds” (B.O.F.) of the Ghent University.


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Copyright information

© International Federation for Medical and Biological Engineering 2008

Authors and Affiliations

  • Guillaume Crevecoeur
    • 1
  • Hans Hallez
    • 2
  • Peter Van Hese
    • 2
  • Yves D’Asseler
    • 2
  • Luc Dupré
    • 1
  • Rik Van de Walle
    • 2
  1. 1.Department of Electrical Energy, Systems and AutomationGhent UniversityGhentBelgium
  2. 2.Department of Electronics and Information SystemsGhent UniversityGhentBelgium

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