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Spatio-temporal ECG analysis for localization of arrhythmias using precordial ECG leads and 128-lead systems.

机译：使用心前区心电图导联和128导联系统进行时空ECG分析以定位心律不齐。

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摘要

A novel and state-of-the-art approach for the analysis of cardiac arrhythmias is proposed. Currently, the analysis of the electrocardiogram is only performed in the time-domain. The proposed method improves the electrocardiogram analysis by adding spatial properties. The spatial properties added to the electrocardiogram allow for the analysis of specific regions inside the human heart where cardiac arrhythmias are suspected to have occurred. In this dissertation, the concept of electrocardiography was extended using advanced bioelectromagnetism theory. In concrete, the multiple dipole model of the human heart was used to extend the concept of electrocardiography from a temporal analysis to a spatial-temporal analysis. The multiple dipole model of the human heart allows analyzing a specific region of the heart. Therefore, it characterizes the electrical activity of that particular region. The spatial analysis, useful for clinical application, was achieved by using a statistical analysis with a population of normal and abnormal patients. The population of normal patients was used to determine the normal range parameters produced by the multiple dipole analysis. The hypothesis behind this dissertation is that abnormal patients lie outside the statistical normal range of the values produced by the multiple dipole analysis. In turn, identifying abnormal patients with this process allows determining the region inside the heart that was found to be abnormal. Four different experiments were performed. The complete cardiac cycle was analyzed, as well as the P-wave, the QRS complex, and the T-wave. A total population of 52 normal patients and 52 abnormal patients was used for the statistical analysis. An efficiency of 80% was found for identifying normal patients. An efficiency of 96%, 36%, 92.3076% and 90.38.46% was found for identifying abnormal patients for the complete cardiac cycle, the P-wave, the QRS complex and the T-wave, respectively. It was found that the proposed method is sensitive to the signal-to-noise ratio and cannot provide an accurate analysis of signals that have a low signal-to-noise ratio, such as the P-wave. The proof of concept explored in this dissertation provided expected results and they indicate that this method could be applied in a clinical trial with a larger population. Therefore, the goals of this dissertation were achieved.
机译：提出了一种新颖的，最新的心律失常分析方法。当前，仅在时域中执行心电图分析。所提出的方法通过增加空间特性来改进心电图分析。添加到心电图上的空间特性可以分析怀疑怀疑发生心律不齐的人心脏内部的特定区域。本文利用先进的生物电磁学理论扩展了心电图学的概念。具体而言，人类心脏的多偶极子模型用于将心电图学的概念从时间分析扩展到时空分析。人心脏的多偶极子模型可以分析心脏的特定区域。因此，它表征了该特定区域的电活动。通过对一群正常和异常患者进行统计分析，实现了对临床应用有用的空间分析。正常患者人群用于确定由多偶极分析产生的正常范围参数。本文的假设是，异常患者处于由多偶极分析得出的值的统计正常范围之外。继而，通过此过程识别异常患者，可以确定被发现异常的心脏内部区域。进行了四个不同的实验。分析了完整的心动周期，以及P波，QRS波群和T波。统计总人数为52例正常患者和52例异常患者。发现识别正常患者的效率为80％。分别以96％，36％，92.3076％和90.38.46％的效率来识别异常患者的完整心动周期，P波，QRS复合波和T波。发现所提出的方法对信噪比敏感，并且不能提供对具有低信噪比的信号（例如P波）的准确分析。本文所探讨的概念验证提供了预期的结果，并表明该方法可用于人群较大的临床试验。因此，达到了本文的目的。

著录项

  • 作者

    Morales, Eduardo.;

  • 作者单位

    The University of Texas at El Paso.;

  • 授予单位 The University of Texas at El Paso.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 94 p.
  • 总页数 94
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 语言学;
  • 关键词

  • 入库时间 2022-08-17 11:38:25

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