Empirical mode decomposition (EMD) for multi-gate, multi-transducer ultrasound Doppler fetal heart monitoring

D. Rouvre, D. Kouamé, F. Tranquart, L. Pourcelot
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引用次数: 17

Abstract

This paper presents a new technique called empirical mode decomposition (EMD) applied to a multi-gate, multitransducer ultrasound Doppler system used for fetal heart monitoring. We propose this system as an alternative to the existing fetal monitoring techniques. Classical autocorrelation-based fetal heart rate (FHR) detection has been shown to be a good method to detect the FHR in normal situations. However, as this method is applied to magnitudes of the Doppler signal fails to estimate the fetal heart rate when the fetus moves. In view of the extent of FHR variability, a monitoring system should be able to estimate this parameter each time. We therefore propose empirical mode decomposition as an interesting alternative for long-term monitoring. The principle of this method consists of iterative decompositions of a signal into a sum of functions that have the same number of extrema, the same number of zero crossings, and are symmetric with respect to the local mean. When investigation of FHR using autocorrelation on the original Doppler signal fails due to fetal movement or low signal-to-noise ratio (SNR), it is frequently successful using the intrinsic mode functions (imfs). We compared the results of multi-transducer FHR detection with and without EMD decomposition using in-vivo Doppler signals from a set of 40 women between 32 and 38 weeks of pregnancy. This method greatly improved the quality of FHR detection
多门多换能器超声多普勒胎儿心脏监测的经验模态分解(EMD)
本文提出了一种应用于多通道、多换能器超声多普勒系统的经验模态分解(EMD)新技术。我们提出这个系统作为替代现有的胎儿监测技术。经典的基于自相关的胎儿心率(FHR)检测已被证明是一种检测正常情况下胎儿心率的好方法。然而,由于该方法应用于多普勒信号的幅度,无法估计胎儿运动时的胎儿心率。鉴于FHR变异性的程度,监测系统每次都应能够估计这一参数。因此,我们提出经验模态分解作为长期监测的有趣替代方案。该方法的原理是将一个信号迭代分解为具有相同极值数、相同过零次数、且相对于局部均值对称的函数和。当由于胎儿运动或低信噪比(SNR)导致原始多普勒信号的自相关研究失败时,使用本征模态函数(imfs)通常是成功的。我们比较了40名怀孕32至38周的妇女体内多普勒信号在EMD分解和未分解情况下的多传感器FHR检测结果。该方法大大提高了FHR检测的质量
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