Marzbanrad Faezeh, Khandoker Ahsan H, Funamoto Kiyoe, Sugibayashi Rika, Endo Miyuki, Velayo Clarissa, Kimura Yoshitaka, Palaniswami Marimuthu
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:3893-6. doi: 10.1109/EMBC.2013.6610395.
In this paper a new noninvasive method is proposed for automated estimation of opening and closure timings of fetal cardiac valves. These timings are obtained from Doppler Ultrasound (DUS) signal and fetal electrocardiogram (fECG) as a reference. Empirical Mode Decomposition (EMD) is first applied to the DUS signal to decompose it into different components called Intrinsic Mode Functions (IMFs). The envelope of the first IMF is then taken and its peaks are identified. The opening and closure of the valves are then automatically assigned to the IMF peaks by using Hidden Markov Model (HMM). It is shown that this new method can continuously evaluate fetal cardiac valves' (aortic and mitral) motion timings for 82.5~99.7% of cardiac cycles. The estimated timings are verified using the Pulsed Doppler images. These findings can be used as sensitive markers for evaluating the fetal cardiac performance.
本文提出了一种新的无创方法,用于自动估计胎儿心脏瓣膜的开闭时间。这些时间是从多普勒超声(DUS)信号和胎儿心电图(fECG)中获取作为参考的。首先将经验模态分解(EMD)应用于DUS信号,将其分解为称为固有模态函数(IMF)的不同分量。然后获取第一个IMF的包络并识别其峰值。接着使用隐马尔可夫模型(HMM)将瓣膜的开闭自动分配给IMF峰值。结果表明,这种新方法能够在82.5%至99.7%的心动周期内持续评估胎儿心脏瓣膜(主动脉瓣和二尖瓣)的运动时间。使用脉冲多普勒图像对估计的时间进行了验证。这些发现可作为评估胎儿心脏功能的敏感指标。