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Atrial Activity Signal Reconstruction Based on Two-sided AR model

机译:基于双面AR模型的心房活动信号重建

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With the rapid development of mobile communication techniques, various mobile health applications are springing up, where the single-lead atrial activity (AA) signal extraction method is urgently required. However, due to QRS residuals, the extracted AA signals by most existing methods are heavily distorted. In this paper, started from signal reconstruction perspective, a novel autoregressive (AR) model based method is presented. Two-sided AA samples around QRS segment are first modeled by AR model, and then the samples in QRS segment are reconstructed using the extrapolation formula. The experimental results on both simulated and real electrocardiograms with atrial fibrillation show that, after using the proposed method, QRS residuals were significantly reduced.
机译:随着移动通信技术的飞速发展,各种移动健康应用如雨后春笋般出现,其中迫切需要单导联心房活动(AA)信号提取方法。然而,由于QRS残差,大多数现有方法提取的AA信号严重失真。本文从信号重建的角度出发,提出了一种基于自回归模型的新方法。首先利用AR模型对QRS段周围的两面AA样本进行建模,然后使用外推公式重建QRS段中的样本。心房颤动的模拟心电图和真实心电图的实验结果表明,使用所提出的方法后,QRS残留量显着降低。

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