无创胎儿心电图中临床信息的提取
Extraction of clinical information from the non-invasive fetal electrocardiogram
摘要：
在上个世纪，胎儿心率（FHR）的估计已经引起了人们的兴趣，低心率变异性已经被研究以识别宫内生长受限胎儿（胎儿），并且异常的FHR模式与分娩期间的胎儿窘迫（产时）有关。已经提出了几种用于FHR估计的监测技术，包括听诊和多普勒超声。本文主要研究从有限的腹部传感器中提取无创胎儿心电图。NI-FECG提取技术的主要挑战是FECG信号在腹部混合信号上的低信噪比，该腹部混合信号由主要的母体ECG分量、FECG和噪声组成。然而，NI-FECG提供了许多优于替代胎儿监测技术的优点，最重要的一个是能够进行FECG的形态分析的机会，这对于确定观察到的FHR事件是正常的还是病理性的至关重要。为了推进NI-FECG信号处理领域的发展，有必要开发标准化的公共数据库，并对一些已发表的新算法进行基准测试。
英文摘要：
Estimation of the fetal heart rate (FHR) has gained interest in the last century, low heart rate variability has been studied to identify intrauterine growth restricted fetuses (prepartum), and abnormal FHR patterns have been associated with fetal distress during delivery (intrapartum). Several monitoring techniques have been proposed for FHR estimation, including auscultation and Doppler ultrasound. This thesis focuses on the extraction of the non-invasive fetal electrocardiogram (NI-FECG) recorded from a limited set of abdominal sensors. The main challenge with NI-FECG extraction techniques is the low signal-to-noise ratio of the FECG signal on the abdominal mixture signal which consists of a dominant maternal ECG component, FECG and noise. However the NI-FECG offers many advantages over the alternative fetal monitoring techniques, the most important one being the opportunity to enable morphological analysis of the FECG which is vital for determining whether an observed FHR event is normal or pathological. In order to advance the field of NI-FECG signal processing, the development of standardised public databases and benchmarking of a number of published and novel algorithms was necessary.
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