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Multichannel EHG Segmentation for automatically identifying contractions

机译:多通道EHG细分,可自动识别收缩

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In a recent past, several techniques have been developed to analyze the events contained in the electrohysterogram signals (EHG). But, the most of them focused on online methods. In this study, we use online methods like Fractal Dimension, Wavelet transform technique, Dynamic Cumulative Sum (DCS). Methods were applied on synthetic signals and real labeled EHG signals database acquiring using $4 x 4$ electrodes matrix. For this purpose, three parameters affecting the Fractal dimension method, the size of analyzing window, thresholding value and the window overlapping, were first tuned in order to identify the recommended values for ruptures detection of the EHG signals by comparing results to its label. According to the obtained results, these three methods seem to be encouraging methods that could be used for automatic ruptures segmentation.
机译:在最近的过去中,已经开发了几种技术来分析包含在电子宫波图信号(EHG)中的事件。但是,大多数都集中在在线方法上。在这项研究中,我们使用分形维数,小波变换技术,动态累积和(DCS)等在线方法。将方法应用于合成信号和使用$ 4 x 4 $电极矩阵采集的真实标记EHG信号数据库。为此,首先调整影响分形维数方法的三个参数,即分析窗口的大小,阈值和窗口重叠,以便通过将结果与其标签进行比较来确定EHG信号破裂检测的推荐值。根据获得的结果,这三种方法似乎是可用于自动破裂分割的令人鼓舞的方法。

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