Clifford小波用于胎儿ECG的提取
Clifford wavelets for fetal ECG extraction
摘要：
在怀孕期间分析胎儿心率对于监测胎儿的正常发育至关重要。目前的胎心监护技术在胎心率监测和特征获取方面缺乏准确性，导致诊断医学问题。挑战在于在怀孕期间从母亲的ECG提取胎儿ECG。这种方法的优点是可靠和非侵入性的技术。为此，本文提出了一种小波/多小波方法，可以完美地提取胎儿心电参数从腹部母亲的心电图。该方法基本上是由于开发Clifford小波作为该领域的最新变体。我们证明了这些小波是更有效的，执行对经典的。因此，实验结果是由于两个基本类的小波和多小波。第一类是经典的Haar Schauder，第二类是Clifford值小波和多小波。这些结果表明，小波/多小波已经是很好的基础，胎儿心电图处理，如果Clifford的是最好的。
英文摘要：
Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the fetal ECG from the mother's ECG during pregnancy. This approach has the advantage of being a reliable and non-invasive technique. For this aim, we propose in this paper a wavelet/multi-wavelet method allowing to extract perfectly the feta ECG parameters from the abdominal mother ECG. The method is essentially due to the exploitation of Clifford wavelets as recent variants in the field. We prove that these wavelets are more efficient and performing against classical ones. The experimental results are therefore due to two basic classes of wavelets and multi-wavelets. A first-class is the classical Haar Schauder, and a second one is due to Clifford valued wavelets and multi-wavelets. These results showed that wavelets/multiwavelets are already good bases for the FECG processing, provided that Clifford ones are the best.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
