On the geometrical sensitivity of the EEG inversion algorithm.
Abstract
The relative algorithms existing in medical devices for the
identification of excitation sources inside the brain using EEG data are
based on the assumption that the geometry of the brain-head system is
spherical. So, taking EEG measurements from a realistic ellipsoidal
model and using these data in a spherical model leads to a structural
error. The purpose of the present work is to estimate this geometrical
error. The results show that for ellipsoids with small principal
eccentricities the errors are not significant. However these errors
become bigger as the eccentricities increase and this is a general
result that becomes available for any related applications of this
inverse problem.