Spatio-temporal EEG dipole estimation by means of a hybrid genetic algorithm

Author

Zou, Ling ; Zhu, Shanan ; He, Bin

Author_Institution

Coll. of Electr. Eng., Zhejiang Univ., Hangzhou, China

Volume

2

fYear

2004

fDate

1-5 Sept. 2004

Firstpage

4436

Lastpage

4439

Abstract

EEG source localization can be considered as a nonlinear optimization process. In the present study, a hybrid genetic algorithm (HGA) is introduced, which combines genetic and local search strategies to overcome the disadvantages of conventional genetic algorithm and local optimization methods. This HGA algorithm was used to localize two dipoles from scalp EEG, and yielded localization accuracy range of 0.95cm-1.55cm when the noise level is within 15%, which is better than the Simplex and GA algorithms in localizing multiple dipoles.

Keywords

electroencephalography; genetic algorithms; medical signal processing; spatiotemporal phenomena; EEG source localization; Simplex algorithm; hybrid genetic algorithm; nonlinear optimization; spatio-temporal EEG dipole estimation; Biological cells; Brain modeling; Electrodes; Electroencephalography; Genetic algorithms; Inverse problems; Optimization methods; Scalp; Search methods; Time measurement; EEG; GA; HGA; source localization;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-8439-3

Type

conf

DOI

10.1109/IEMBS.2004.1404233

Filename

1404233