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Removal of baseline wander from ECG signal using cascaded Empirical Mode Decomposition and morphological functions

机译:使用级联的经验模态分解和形态函数从ECG信号中消除基线漂移

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The ECG is a record of the electrical activities of the heart. It is used for the diagnosis of a number of cardiac defects such as arrhythmias, AF etc. Quite often they get corrupted by various kinds of artifacts, thus in order to obtain proper information from them they must first be denoised. Baseline wander artifact is one of the most common artifact of ECG. This paper presents a novel approach for the filtering of low frequency baseline wander artifact of ECG signals by using a combination of Empirical Mode Decomposition (EMD) and morphological functions. By using this novel approach for denoising of baseline wander artifact, it is ensured that morphological information from the ECG signal remain preserved.
机译:心电图是心脏电活动的记录。它用于诊断许多心律失常,例如心律不齐,房颤等。它们经常会因各种伪影而受损,因此,为了从它们中获取正确的信息,必须首先对其进行消噪处理。基线漂移伪影是ECG最常见的伪影之一。本文提出了一种新的方法,通过结合经验模式分解(EMD)和形态函数来过滤ECG信号的低频基线漂移假象。通过使用这种新颖的方法对基线漂移伪影进行降噪,可以确保保留来自ECG信号的形态信息。

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