• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2010 3rd International Conference on Biomedical Engineering and Informatics >Classification of Electroencephalogram signals using Artificial Neural Networks
【24h】

Classification of Electroencephalogram signals using Artificial Neural Networks

机译：使用人工神经网络对脑电图信号进行分类

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The study of Artificial Neural Networks (ANN) has been fascinating over the years and its development has strongly grown in recent years. The neural networks methods have become to be increasingly convincing for solving complex problems, through artificial intelligence. In particular, this work, focused on the development of an artificial neural network for identifying diseases: Parkinson's, Huntington's and Amyotrophic Lateral Sclerosis, based on signals from the Electroencephalogram (EEG). The project was developed through a number of operations implemented in Matlab. The Fourier transform was seen as the main technique of signal processing, in order to analyze and diagnose diseases in the study. The work consisted first in the EEG signals to serve as an entry into the ANN in order to reveal a distinctive feature in the different diseases, and then, create an ANN architecture capable to distinguish the diseases. For this purpose 4 methodologies were used with different processing of the EEG signal. The 4 methodologies are compared in this paper.
机译：多年来，人工神经网络（ANN）的研究一直很引人入胜，并且近年来其发展迅速。神经网络方法通过人工智能解决复杂问题变得越来越具有说服力。尤其是，这项工作着重于开发基于神经电图（EEG）信号的用于识别疾病的人工神经网络：帕金森氏症，亨廷顿氏症和肌萎缩性侧索硬化症。该项目是通过在Matlab中实施的许多操作开发的。为了分析和诊断研究中的疾病，傅里叶变换被视为信号处理的主要技术。该工作首先包括在EEG信号中，作为进入ANN的入口，以揭示不同疾病的独特特征，然后创建一个能够区分疾病的ANN体系结构。为此，使用了4种方法来处理EEG信号。本文比较了这4种方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号