@Article{IJNAM-13-4,
author = {},
title = {Assessment of Two Approximation Methods for the Inverse Problem of Electroencephalography},
journal = {International Journal of Numerical Analysis and Modeling},
year = {2016},
volume = {13},
number = {4},
pages = {587--609},
abstract = {<p style="text-align: justify;">The goal of this paper is to compare two computational models for the inverse
problem of electroencephalography: the localization of brain activity from measurements of the
electric potential on the surface of the head. The source current is modeled as a dipole whose
localization and polarization has to be determined. Two methods are considered for solving the
corresponding forward problems: the so called subtraction approach and direct approach. The
former is based on subtracting a fundamental solution, which has the same singular character of
the actual solution, and solving computationally the resulting non-singular problem. Instead, the
latter consists in solving directly the problem with singular data by means of an adaptive process
based on an a posteriori error estimator, which allows creating meshes appropriately refined around
the singularity. A set of experimental tests for both, the forward and the inverse problems, are
reported. The main conclusion of these tests is that the direct approach combined with adaptivity
is preferable when the localization of the dipole is close to an interface between brain tissues with
different conductivities.</p>},
issn = {2617-8710},
doi = {https://doi.org/2016-IJNAM-454},
url = {https://global-sci.com/article/83253/assessment-of-two-approximation-methods-for-the-inverse-problem-of-electroencephalography}
}