@inproceedings{412e48055ac544bbb4e89f1c9d5945c5,
title = "Development of Alzheimer's disease detection and analysis system using brain signals of Alzheimer model animals",
abstract = "This study is to develop the Alzheimer's disease (AD) detection and analysis system using brain signals including EEG (electroencephalogram) and ERP (event-related potential) of AD model animals. We analyzed the chaotic features as well as spectral and statistical features of the signals to make a feature pool. The genetic a lgorithm (GA) and artificial neural network (ANN) were applied to find a minimal set of the dominant features from the feature pool that are used as an optimal inputs of the artificial neural network to classify the AD and normal animals. The combined GA/ANN approach could be extended to a reliable classification system using EEG recording that can discriminate between groups.",
keywords = "Alzheimer's disease, Artificial neural network, Electroencephalogram, Genetic algorithms",
author = "Sunyoung Cho and Insop Shim and Kim, {Jong Woo} and Hwang, {Eui Whan} and Kim, {Hyun Taek}",
note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; Proceedings of the International Conference on Mathematics and Engineering Techniques in medicine and Biological Sciences, METMBS'04 ; Conference date: 21-06-2004 Through 24-06-2004",
year = "2004",
language = "English",
isbn = "1932415432",
series = "Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, METMBS'04",
pages = "135--138",
editor = "F. Valafar and H. Valafar",
booktitle = "Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, METMBS'04",
}