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Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation

机译:心房颤动过程中嘈杂的心电图的样本熵分析

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摘要

Most cardiac arrhythmias can be classified as atrial flutter, focal atrial tachycardia, or atrial fibrillation. They have been usually treated using drugs, but catheter ablation has proven more effective. This is an invasive method devised to destroy the heart tissue that disturbs correct heart rhythm. In order to accurately localise the focus of this disturbance, the acquisition and processing of atrial electrograms form the usual mapping technique. They can be single potentials, double potentials, or complex fractionated atrial electrogram (CFAE) potentials, and last ones are the most effective targets for ablation. The electrophysiological substrate is then localised by a suitable signal processing method. Sample Entropy is a statistic scarcely applied to electrograms but can arguably become a powerful tool to analyse these time series, supported by its results in other similar biomedical applications. However, the lack of an analysis of its dependence on the perturbations usually found in electrogram data, such as missing samples or spikes, is even more marked. This paper applied SampEn to the segmentation between non-CFAE and CFAE records and assessed its class segmentation power loss at different levels of these perturbations. The results confirmed that SampEn was able to significantly distinguish between non-CFAE and CFAE records, even under very unfavourable conditions, such as 50% of missing data or 10% of spikes.
机译:大多数心律不齐可分为房扑,局灶性心动过速或房颤。通常使用药物对其进行治疗,但是导管消融已被证明更有效。这是一种旨在破坏破坏正确心律的心脏组织的侵入性方法。为了准确定位此干扰的焦点,心电图的获取和处理形成了常规的映射技术。它们可以是单电位,双电位或复杂的心房电描记图(CFAE)电位,最后一个是最有效的消融靶标。然后通过合适的信号处理方法定位电生理底物。样本熵是很少应用于电描记图的统计数据,但可以说是分析这些时间序列的有力工具,并在其他类似的生物医学应用中得到了结果支持。但是,缺乏对电描记图数据中通常会发现的扰动(例如丢失样本或尖峰)的依赖性的分析,这一点更加明显。本文将SampEn应用于非CFAE和CFAE记录之间的分割,并评估了在这些扰动的不同级别下其类别分割功率损耗。结果证实,即使在非常不利的条件下(例如丢失数据的50%或峰值的10%),SampEn仍能够显着区分非CFAE和CFAE记录。

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