Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings
Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings
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DOI：
10.1109/tbme.2003.808824
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发表时间：
2003-03-01
影响因子：
4.6
通讯作者：
Arduini, D
中科院分区：
文献类型：
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作者：
Signorini, MG;Magenes, G;Arduini, D
基于经典胎心监护（CTG）的产前胎儿监测是一种无创且简单的胎儿状态检查工具。它在临床常规中的引入限制了胎儿问题的发生，从而降低了早熟儿童的死亡率。然而，即使从实际使用的自动 CTG 分析方法中也可以推断出对胎儿病理学的非常差的指示。感觉胎心率 (FHR) 信号和子宫收缩携带的胎儿状态信息比通常通过经典分析方法提取的信息要多得多。特别是，胎心率信号包含有关胎儿神经发育的指示。然而，实际采用的判断 CTG 迹线“异常”的方法对胎儿危险的预测指示较弱。我们提出了一种基于多参数胎心率分析的 CTG 监测新方法，其中包括来自自回归模型和非线性算法（近似熵）的光谱参数。这项初步研究考虑了 14 个正常胎儿、8 个妊娠（母体）糖尿病病例和 13 个宫内生长迟缓胎儿。还包括与传统时域分析的比较。本文表明，所提出的新参数能够区分正常胎儿和病理胎儿。结果构成了实现用于早期诊断最常见胎儿病理的新临床分类系统的第一步。
Antepartum fetal monitoring based on the classical cardiotocography (CTG) is a noninvasive and simple tool for checking fetal status. Its introduction in the clinical routine limited the occurrence of fetal problems leading to a reduction of the precocious child mortality. Nevertheless, very poor indications on fetal pathologies can be inferred from the even automatic CTG analysis methods, which are actually employed. The feeling is that fetal heart rate (FHR) signals and uterine contractions carry much more information on fetal state than is usually extracted by classical analysis methods. In particular, FHR signal contains indications about the neural development of the fetus. However, the methods actually adopted for judging a CTG trace as "abnormal" give weak predictive indications about fetal dangers. We propose a new methodological approach for the CTG monitoring, based on a multiparametric FHR analysis, which includes spectral parameters from autoregressive models and nonlinear algorithms (approximate entropy). This preliminary study considers 14 normal fetuses, eight cases of gestational (maternal) diabetes, and 13 intrauterine growth retarded fetuses. A comparison with the traditional time domain analysis is also included. This paper shows that the proposed new parameters are able to separate normal from pathological fetuses. Results constitute the first step for realizing a new clinical classification system for the early diagnosis of most common fetal pathologies.