Lee Kwang Jin, Lee Boreom
Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea.
Sensors (Basel). 2016 Jul 1;16(7):1020. doi: 10.3390/s16071020.
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.
胎儿心率(FHR)是胎儿健康的重要决定因素。产时胎心监护(CTG)在临床领域被广泛用于测量胎儿心率。然而,胎儿运动和通过母体血管的血流会严重影响多普勒超声信号。此外,CTG不适用于长期监测。因此,研究人员一直在开发利用孕妇腹部心电图(ECG)来估计胎儿心率的算法。然而,从腹部ECG信号中分离出微弱的胎儿ECG信号是一个具有挑战性的问题。在本文中,我们提出一种使用序列全变差去噪来估计胎儿心率的方法,并通过使用胎儿心电图合成数据库(FECGSYNDB)进行模拟,将其性能与其他单通道胎儿ECG提取方法的性能进行比较。此外,我们使用来自PhysioNet胎儿ECG数据库的真实数据来评估算法性能。通过计算R波检测率来评估我们算法的性能。我们的方法不仅可以从腹部ECG信号中分离出胎儿ECG信号,还能准确估计胎儿心率。