论文标题
一种使用自适应过滤器的仿生组合提取胎儿心电图的新方法
A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters
论文作者
论文摘要
怀孕期间发现异常的胎儿心跳对于监测胎儿的健康状况很重要。尽管成人心电图在现代医学方面取得了一些进步，但无创胎儿心电图（FECG）仍然是一个巨大的挑战。在本文中，我们引入了一种基于自适应过滤器的仿射组合来提取FECG信号的新方法。多个过滤器的仿射组合能够准确地拟合参考信号，从而获得更准确的FECG。我们提出了一种结合最小平方（LMS）和递归最小二乘（RLS）过滤器的方法。我们的方法发现，合并的递归最小二乘（CRL）滤波器在所有提出的组合中都能达到最佳性能。此外，我们发现CRLs从具有较小的信噪比（SNR）的腹部心电图（AECG）中提取FECG更有利。与最先进的无国界医生法相比，CRLS显示出改善的性能。灵敏度，准确性和F1的得分分别提高了3.58％，2.39％和1.36％。
The detection of abnormal fetal heartbeats during pregnancy is important for monitoring the health conditions of the fetus. While adult ECG has made several advances in modern medicine, noninvasive fetal electrocardiography (FECG) remains a great challenge. In this paper, we introduce a new method based on affine combinations of adaptive filters to extract FECG signals. The affine combination of multiple filters is able to precisely fit the reference signal, and thus obtain more accurate FECGs. We proposed a method to combine the Least Mean Square (LMS) and Recursive Least Squares (RLS) filters. Our approach found that the Combined Recursive Least Squares (CRLS) filter achieves the best performance among all proposed combinations. In addition, we found that CRLS is more advantageous in extracting FECG from abdominal electrocardiograms (AECG) with a small signal-to-noise ratio (SNR). Compared with the state-of-the-art MSF-ANC method, CRLS shows improved performance. The sensitivity, accuracy, and F1 scores improved by 3.58%, 2.39%, and 1.36%, respectively.
