首页> 外文会议>International conference on latent variable analysis and signal separation >Source Analysis and Selection Using Block Term Decomposition in Atrial Fibrillation
【24h】

Source Analysis and Selection Using Block Term Decomposition in Atrial Fibrillation

机译:心房颤动中使用术语分解的源分析和选择

获取原文

摘要

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in clinical practice, and is becoming a major public health concern. To better understand the mechanisms of this arrhythmia an accurate analysis of the atrial activity (AA) signal in electrocardiogram (ECG) recordings is necessary. The block term decomposition (BTD), a tensor factorization technique, has been recently proposed as a tool to extract the AA in ECG signals using a blind source separation (BSS) approach. This paper makes a deep analysis of the sources estimated by BTD, showing that the classical method to select the atrial source among the other sources may not work in some cases, even for the matrix-based methods. In this context, we propose two new automated methods to select the atrial source by considering another novel parameter. Experimental results on ten patients show the validity of the proposed methods.
机译:心房颤动(AF)是临床实践中最常见的持续性心律不齐,并且正成为主要的公共卫生问题。为了更好地了解这种心律失常的机制,有必要对心电图(ECG)记录中的心房活动(AA)信号进行准确的分析。最近已经提出了张量分解技术-块项分解(BTD),作为一种使用盲源分离(BSS)方法在ECG信号中提取AA的工具。本文对BTD估算的源进行了深入分析,表明在某些情况下,即使对于基于矩阵的方法,在其他源中选择房源的经典方法也可能不起作用。在这种情况下,我们提出了两种新的自动化方法来通过考虑另一个新参数来选择心房来源。对十名患者的实验结果证明了所提出方法的有效性。

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