• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >An algorithm for on-line detection of high frequency oscillations related to epilepsy
【24h】

An algorithm for on-line detection of high frequency oscillations related to epilepsy

机译：在线检测与癫痫有关的高频振荡的算法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Recent studies suggest that the appearance of signals with high frequency oscillations components in specific regions of the brain is related to the incidence of epilepsy. These oscillations are in general small in amplitude and short in duration, making them difficult to identify. The analysis of these oscillations are particularly important in epilepsy and their study could lead to the development of better medical treatments. Therefore, the development of algorithms for detection of these high frequency oscillations is of great importance. In this work, a new algorithm for automatic detection of high frequency oscillations is presented. This algorithm uses approximate entropy and artificial neural networks to extract features in order to detect and classify high frequency components in electrophysiological signals. In contrast to the existing algorithms, the one proposed here is fast and accurate, and can be implemented on-line, thus reducing the time employed to analyze the experimental electrophysiological signals.
机译：最近的研究表明，在大脑的特定区域出现具有高频振荡成分的信号与癫痫的发生有关。这些振荡通常幅度小且持续时间短，从而使其难以识别。对这些振荡的分析在癫痫中尤为重要，对它们的研究可能会导致更好的医学治疗方法的发展。因此，开发用于检测这些高频振荡的算法非常重要。在这项工作中，提出了一种自动检测高频振荡的新算法。该算法使用近似熵和人工神经网络来提取特征，以便检测和分类电生理信号中的高频成分。与现有算法相比，此处提出的算法快速，准确，并且可以在线实施，从而减少了用于分析实验电生理信号的时间。

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