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A New Algorithm for Removal Baseline Wander in ECG Signal Based on Empirical Mode Decomposition

机译:基于经验模态分解的消除心电信号基线漂移的新算法

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Removal of baseline wander in ECG signal is a classical problem. In this paper, we propose a new method for removing the baseline wander interferences based on Empirical Mode Decomposition (EMD). The method is very sensitive to end conditions, that is, the end effect. We propose a novel method to restrict the end effect and improve the precision of EMD. EMD can adaptively decompose ECG signal into a series of Intrinsic Mode Functions. The baseline wander is mainly involved in special IMFs. Then selective reconstruction is performed to restore the "clean" ECG signal. To evaluate the performance of the method, Clinic ECG signals are used. Results indicate that the method is powerful and useful in removing the baseline wander in ECG signal and does not distort the ECG signal.
机译:消除ECG信号中的基线漂移是一个经典问题。在本文中,我们提出了一种基于经验模式分解(EMD)的消除基线漂移干扰的新方法。该方法对最终条件(即最终效果)非常敏感。我们提出了一种新的方法来限制最终效果并提高EMD的精度。 EMD可以将ECG信号自适应地分解为一系列固有模式函数。基线波动主要涉及特殊的IMF。然后执行选择性重建以恢复“干净”的ECG信号。为了评估该方法的性能,使用了临床ECG信号。结果表明,该方法在消除ECG信号的基线漂移方面功能强大且有用,并且不会使ECG信号失真。

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