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Evaluating the fetal heart rate baseline estimation algorithms by their influence on detection of clinically important patterns

机译:通过其对临床重要模式检测的影响来评估胎儿心率基线估计算法

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A correctly estimated component of fetal heart rate signal (FHR) - so called baseline - is a precondition for proper recognition of acceleration and deceleration patterns. A number of various algorithms for estimating the FHR baseline was proposed so far. However, there is no reference standard enabling their objective evaluation, and thus no methodology of comparing the different algorithms still exists. In this paper we propose a method for evaluation of automatically determined baseline in reference to a set of experts, based on ten separate groups of signals comprising typical variability patterns observed in the fetal heart rate. As it was proposed earlier [1], the given algorithm is evaluated based on the characteristic patterns detected using the obtained baseline, instead of direct analysis of the baseline shape. For the purpose of quantitative assessment of the estimated baseline a new synthetic inconsistency coefficient was applied. The proposed methodology enabled to evaluate eleven well-known algorithms. We believe that the method will be a valuable tool for assessment of the existing algorithms, as well as for developing the new ones. (C) 2016 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier Sp. z o. o. All rights reserved.
机译:正确估计的胎儿心率信号(FHR)分量-所谓的基线-是正确识别加速和减速模式的前提。到目前为止,已经提出了许多用于估计FHR基线的算法。但是,没有参考标准可以对其进行客观评估,因此还不存在比较不同算法的方法。在本文中,我们基于一组十组信号(包括在胎儿心率中观察到的典型变异模式),提出了一种参考一组专家评估自动确定基线的方法。如更早提出的[1],将基于使用获得的基线检测到的特征模式来评估给定算法,而不是直接分析基线形状。为了定量评估估计的基线,应用了新的综合不一致系数。所提出的方法能够评估11种众所周知的算法。我们相信,该方法将是评估现有算法以及开发新算法的宝贵工具。 (C)2016年波兰科学院纳勒奇生物cybernetics和生物医学工程研究所。由Elsevier Sp。发行。则o。版权所有。

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