Non-invasive EEG source localization using particle swarm optimization: A clinical experiment
Paper in proceeding, 2012
One of the most important steps of pre-surgical diagnosis in patients with medically intractable epilepsy is to find the precise location of the epileptogenic foci. An Electroencephalography (EEG) is a non-invasive standard tool used at epilepsy surgery center for pre-surgical diagnosis. In this paper a modified particle swarm optimization (MPSO) method is applied to a real EEG data, i.e., a somatosensory evoked potentials (SEPs) measured from a healthy subject, to solve the EEG source localization problem. A high resolution 1 mm hexahedra finite element volume conductor model of the subject's head was generated using T1-weighted magnetic resonance imaging data. An exhaustive search pattern and the MPSO method were then applied to the peak of the averaged SEPs data. The non-invasive EEG source analysis methods localized the somatosensory cortex area where our clinical expert expected the received SEPs. The proposed inverse problem solver found the global minima with acceptable accuracy and reasonable number of iterations.
High resolution
Global minima
Epileptogenic foci
Somatosensory cortex
Modified particle swarm optimization
EEG source localization
Somatosensory evoked potentials
Epilepsy surgery
Finite Element
Source analysis method
Number of iterations
T1-weighted magnetic resonance imaging
Exhaustive search
Healthy subjects
Standard tools
Author
Yazdan Shirvany
Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering
Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering
Johan Carlson
Fraunhofer-Chalmers Centre
Stefan Jakobsson
Fraunhofer-Chalmers Centre
Anders Hedström
University of Gothenburg
Mahmood Qaiser
Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering
Artur Chodorowski
Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering
Mikael Persson
Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
1557170X (ISSN)
6232-6235 6347418978-142444119-8 (ISBN)
Subject Categories
Medical Engineering
DOI
10.1109/EMBC.2012.6347418
ISBN
978-142444119-8