Localization of an inert region in the brain using modified Levenberg Marquarts neural network

Katayama, Masato, Akutagawa, Masatake, Abeyratne, Udantha R., Kaji, Yoshio, Schichijo, Fumio, Nagashino, Hirofumi and Kinouchi, Yohsuke (2007). Localization of an inert region in the brain using modified Levenberg Marquarts neural network. In: Dittmar, A. and Clark, J., Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2007), Lyon, France, (4098-4101). 23-26 August 2007. doi:10.1109/IEMBS.2007.4353237


Author Katayama, Masato
Akutagawa, Masatake
Abeyratne, Udantha R.
Kaji, Yoshio
Schichijo, Fumio
Nagashino, Hirofumi
Kinouchi, Yohsuke
Title of paper Localization of an inert region in the brain using modified Levenberg Marquarts neural network
Conference name 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2007)
Conference location Lyon, France
Conference dates 23-26 August 2007
Proceedings title Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Journal name 2007 Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-16
Place of Publication Piscataway, USA
Publisher IEEE
Publication Year 2007
Sub-type Fully published paper
DOI 10.1109/IEMBS.2007.4353237
ISBN 9781424407873
1424407885
ISSN 1094-687X
Editor Dittmar, A.
Clark, J.
Start page 4098
End page 4101
Total pages 4
Collection year 2008
Language eng
Abstract/Summary We tested the localization accuracy of electroencephalograph (EEG) for an inert region in a simulation at sizes ranging from 1 to 8 cm at 1 cm intervals. We used international 10-20 system electrodes placements and three concentric shell model to calculate forward problems. From using the data, neural network could be used to solve inverse problems. In this case, we estimate the localization of inert region. To demonstrate the effectiveness of the method, we perform simulations on location of inert region from EEG data, consists of training and test data. Based on the results of extensive studies, we conclude that neural network are high feasible as localization of inert region. These EEG estimation tasks were created by using a set of calculated, artificial EEG signals based on a number of current dipoles. The experimental results indicate that the proposed method has several attractive features. 1) The size of inert region is becoming more large and more the RMS values low. 2) The following the distance is closer, the RMS values is low. That could be considered inert region exists near by the electrode which has low RMS potential. 3) The more larger inert region were, the more small estimation error become. © 2007 IEEE.
Subjects E1
291500 Biomedical Engineering
730110 Respiratory system and diseases (incl. asthma)
Keyword Electroencephalography
Localization of inert region
Modified Levenberg Marquardt
Neural network
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Tue, 06 May 2008, 14:45:03 EST by Donna Clark on behalf of School of Information Technol and Elec Engineering