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Atrial Activity Estimation using Periodic Component Analysis

机译:使用周期性分量分析的心房活动估计

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The interest in the study and analysis of Atrial Fibrillation (AF) has increased significantly in the last decades. A correct estimation of the atrial activity is a crucial previous step for AF analysis. Different methods based on Blind Source Separation of 12-lead electrocardiogram (ECG) have been proposed. However, these techniques are based only on the statistical independence of the sources, and usually require a postprocessing step to identify the signal of interest. We present a method that also uses a multilead approach in order to use all the information available in the leads, but it focuses on the discriminative properties of the spectrum of the atrial signal with respect to the non-atrial components. The atrial rhythm can be considered as a pseudo-periodic signal with a main atrial frequency in the range 3-10 Hz. The bandwidth and shape of the spectrum is related to the patient and the kind of tachyrhythmia. Another advantage is that the way the atrial component is extracted is based on algebraic methods, avoiding the adjustment of learning rates and other parameters. The method is applied successfully to real data.
机译:在过去的几十年中,对心房颤动(AF)的研究和分析的兴趣显着增加。对心房活动的正确估计是AF分析的前一步骤。已经提出了基于12-铅心电图(ECG)盲源分离的不同方法。然而,这些技术仅基于源的统计独立性,并且通常需要后处理步骤来识别感兴趣的信号。我们介绍了一种方法,该方法还使用多地方法,以便使用引线中可用的所有信息,但它专注于心房信号相对于非心房组件的谱的辨别特性。心房节奏可以被认为是伪周期信号,其主节频率在3-10Hz范围内。光谱的带宽和形状与患者和术的类型有关。另一个优点是提取心房组分的方式基于代数方法,避免了学习率的调整和其他参数。该方法成功应用于实际数据。

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