Brain Inert Region Identification from EEG using LM Neural networks
The purpose of this study is to examine the practical effectiveness of neural networks for the localization of an inert region from EEG with multi electrodes arragement of a 10-20 system,also to investigate estimation accuracy in relation to EEG referenes,inert region positions and network training.The developed techniques are then applied to clinical EEG data.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.
neural network electroencephalography localization of inert region modified Levenberg Marquardt
Masato KATAYAMA Masatake AKUTAGAWA Udantha R.Abeyratne Yoshio KAJI Fumio SHICHIJO Hirofumi NAGASHINO Yohsuke KINOUCHI
Faculty of Engineering The Univ.of Tokushima Minamijosanjima Tokushima,770-8506 Japan School of Info.Tech and Electrical Engineering The University of Queensland St Lucia,Brisbane QLD 40 Faculty of Engineering The Univ.of Bunri Sanuki,Kagawa,769-2193,Japan Suzue Medical Center Sacho Tokushima,770-0028 Japan
国际会议
哈尔滨
英文
272-275
2008-01-13（万方平台首次上网日期，不代表论文的发表时间）