Particle Swarm Optimization Applied to EEG Source Localization of Somatosensory Evoked Potentials
Artikel i vetenskaplig tidskrift, 2014

One of the most important steps in presurgical diagnosis of medically intractable epilepsy is to find the precise location of the epileptogenic foci. Electroencephalography (EEG) is a noninvasive tool commonly used at epilepsy surgery centers for presurgical diagnosis. In this paper, a modified particle swarm optimization (MPSO) method is used to solve the EEG source localization problem. The method is applied to noninvasive EEG recording of somatosensory evoked potentials (SEPs) for a healthy subject. A 1 mm hexahedra finite element volume conductor model of the subject's head was generated using T1-weighted magnetic resonance imaging data. Special consideration was made to accurately model the skull and cerebrospinal fluid. An exhaustive search pattern and the MPSO method were then applied to the peak of the averaged SEP data and both identified the same region of the somatosensory cortex as the location of the SEP source. A clinical expert independently identified the expected source location, further corroborating the source analysis methods. The MPSO converged to the global minima with significantly lower computational complexity compared to the exhaustive search method that required almost 3700 times more evaluations.

RECONSTRUCTION

Electroencephalogram (EEG) source localization

ELECTRICAL-STIMULATION

HEAD MODELS

DIPOLE LOCALIZATION

inverse problem

CORTEX

MEDIAN NERVE-STIMULATION

FUNCTIONAL MRI

finite element method (FEM)

FINITE-ELEMENT-METHOD

Författare

Yazdan Shirvany

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Biomedicinsk elektromagnetik

Mahmood Qaiser

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Biomedicinsk elektromagnetik

Johan Carlson

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Stefan Jakobsson

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Anders Hedström

Sahlgrenska akademin

Mikael Persson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

IEEE Transactions on Neural Systems and Rehabilitation Engineering

1534-4320 (ISSN)

Vol. 22 1 11-20 13

Ämneskategorier

Medicinteknik

DOI

10.1109/TNSRE.2013.2281435