...
首页> 外文期刊>Computers in Biology and Medicine >ECG characterization of paroxysmal atrial fibrillation: parameter extraction and automatic diagnosis algorithm.
【24h】

ECG characterization of paroxysmal atrial fibrillation: parameter extraction and automatic diagnosis algorithm.

机译:阵发性房颤的ECG表征:参数提取和自动诊断算法。

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Paroxysmal atrial fibrillation (PAF) is one of the most common heart arrhythmias. It is very difficult to detect unless an explicit Atrial Fibrillation episode occurs during the exploration. The present paper describes a number of low level parameters extracted from ECG traces where no Atrial Fibrillation process is present. The ability of this parameter set to characterize PAF patients is studied and discussed. Based on these parameters a modular automatic classification algorithm for PAF diagnosis is developed and evaluated.
机译:阵发性房颤(PAF)是最常见的心脏心律不齐之一。除非在探索期间发生明确的心房颤动发作,否则很难检测到。本文描述了从不存在心房颤动过程的ECG迹线中提取的许多低级参数。研究和讨论了该参数集表征PAF患者的能力。基于这些参数,开发并评估了用于PAF诊断的模块化自动分类算法。

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