• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>New advances in intelligent signal processing >Advances in Automated Neonatal Seizure Detection
【24h】

Advances in Automated Neonatal Seizure Detection

机译：新生儿癫痫发作自动检测的进展

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

This chapter highlights the current approaches in automated neonatal seizure detection and in particular focuses on classifier based methods. Automated detection of neonatal seizures has the potential to greatly improve the outcome of patients in the neonatal intensive care unit. The electroencephalogram (EEG) is the only signal on which 100% of electrographic seizures are visible and thus is considered the gold standard for neonatal seizure detection. Although a number of methods and algorithms have been proposed previously to automatically detect neonatal seizures, to date their transition to clinical use has been limited due to poor performances mainly attributed to large inter and intra-patient variability of seizure patterns and the presence of artifacts. Here, a novel detector is proposed based on time-domain, frequency-domain and information theory analysis of the signal combined with pattern recognition using machine learning principles. The proposed methodology is based on a classifier with a large and diverse feature set and includes a post-processing stage to incorporate contextual information of the signal. It is shown that this methodology achieves high classification accuracy for both classifiers and allows for the use of soft decisions, such as the probability of seizure over time, to be displayed.
机译：本章重点介绍了新生儿癫痫发作自动检测的当前方法，特别是基于分类器的方法。新生儿癫痫发作的自动检测可能会大大改善新生儿重症监护病房的患者预后。脑电图（EEG）是唯一可见100％的电图癫痫发作的信号，因此被认为是新生儿癫痫发作检测的金标准。尽管先前已经提出了许多方法和算法来自动检测新生儿癫痫发作，但是由于性能差（主要归因于癫痫发作模式在患者之间和患者内部的巨大变异以及伪影的存在），迄今为止，它们向临床应用的过渡受到了限制。在此，基于信号的时域，频域和信息论分析，结合基于机器学习原理的模式识别，提出了一种新颖的检测器。所提出的方法基于具有大量多样特征集的分类器，并包括合并信号上下文信息的后处理阶段。结果表明，该方法对于两个分类器均实现了较高的分类精度，并允许使用软判决（例如随时间推移发生扣押的可能性）进行显示。

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