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A Robust and Non-invasive Fetal Electrocardiogram Extraction Algorithm in a Semi-Blind Way

机译:半盲的鲁棒无创胎儿心电图提取算法

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摘要

Fetal electrocardiogram (FECG) extraction is of vital importance in biomedical signal processing. A promising approach is blind source extraction (BSE) emerging from the neural network fields, which is generally implemented in a semi-blind way. In this paper, we propose a robust extraction algorithm that can extract the clear FECG as the first extracted signal. The algorithm exploits the fact that the FECG signal's kurtosis value lies in a specific range, while the kurtosis values of other unwanted signals do not belong to this range. Moreover, the algorithm is very robust to outliers and its robustness is theoretically analyzed and is confirmed by simulation. In addition, the algorithm can work well in some adverse situations when the kurtosis values of some source signals are very close to each other. The above reasons mean that the algorithm is an appealing method which obtains an accurate and reliable FECG.
机译:胎儿心电图(FECG)提取在生物医学信号处理中至关重要。一种有前途的方法是从神经网络领域出现的盲源提取(BSE),通常以半盲方式实现。在本文中,我们提出了一种鲁棒的提取算法,可以提取清晰的FECG作为第一个提取的信号。该算法利用了以下事实:FECG信号的峰度值处于特定范围内,而其他有害信号的峰度值不属于该范围。此外,该算法对异常值非常鲁棒,并且对其鲁棒性进行了理论分析并通过仿真得到了证实。此外,当某些源信号的峰度值彼此非常接近时,该算法可以在某些不利情况下很好地工作。上述原因意味着该算法是一种获得准确,可靠的FECG的吸引人的方法。

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