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Topographic imaging of the atrial electrical activity during atrial fibrillation for the analysis of uniform distributions of the surface electrical potentials

机译:心房颤动期间心房电活动的地形成像,用于分析表面电势的均匀分布

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Atrial fibrillation (AF) is a progressive arrhythmia which causes time dependent impairing of the cardiac muscle. This makes that proper therapeutic interventions depend on the degree of AF progression, i.e., on the temporal decrease of the organization of the electrical patterns observed during AF. Standard effective treatments are still lacking nowadays, and this calls for suitable noninvasive analysis of AF. In this sense, an appropriate therapy relies on the knowledge of AF characteristics, as its degree of organization. To this purpose, fast and accurate imaging of cardiac electrical activity can be helpful. Relying on the results of previous work on noninvasive assessment of the complexity of AF, we put forward a method to obtain visual maps of the topographic projection of the main atrial activity (AA) component given by principal component analysis, which is shown to provide detailed information about AA potential pattern distributions on the body surface. Different AA potential pattern distributions can then be identified, depending on the underlying degree of AF organization. An automated way to assess AF organization degree is then proposed, based on topographic projections. Similarities with previous studies suggest its usefulness for determining uniform distributions in the activation patterns on the body surface.
机译:心房颤动(AF)是一种进行性心律失常,会导致心肌的时间依赖性损害。这使得适当的治疗干预取决于AF进展的程度,即,取决于在AF期间观察到的电模式的组织的时间减少。如今仍缺乏标准有效的治疗方法,这要求对AF进行适当的非侵入性分析。从这个意义上说,一种适当的治疗方法取决于对房颤特征的了解,以及房颤的组织程度。为此,对心脏电活动进行快速准确的成像可能会有所帮助。根据先前关于房颤复杂性的非侵入性评估工作的结果,我们提出了一种方法来获取主成分分析给出的主要心房活动(AA)成分的地形图的可视化图,该方法可提供详细的信息。有关机体表面AA电位模式分布的信息。然后,根据AF组织的潜在程度,可以识别出不同的AA潜在模式分布。然后提出了一种基于地形预测的自动评估房颤组织程度的方法。与先前研究的相似之处表明,它可用于确定人体表面激活模式中的均匀分布。

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