胎儿心率估计的信号分离算法

Kuei-Chiang Lai, J. Shynk
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引用次数: 4

摘要

在本文中,我们描述了一种自适应算法,用于从包含胎儿和母亲QRS复合物的数据中分离胎儿和母亲的心跳。该算法使用模板匹配技术将合并的心率数据分类为一系列胎儿、母体和噪声事件。峰检测首先用于定位潜在的胎儿和母体QRS复合物(称为候选事件)。从初始化期间的候选事件自动生成胎儿和母体模板,并根据一定的相似性标准对剩余的候选事件进行分类。一旦成功地检测和分离胎儿和母体复合物,就可以利用计数机制来推导相应的心率。实际数据的计算机仿真验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A signal separation algorithm for fetal heart-rate estimation
In this paper we describe an adaptive algorithm for separating fetal and maternal heart beats from data containing both fetal and maternal QRS complexes. The algorithm classifies the combined heart-rate data as a series of fetal maternal, and noise events using a technique of template matching. Peak detection is first employed to locate the potential fetal and maternal QRS complexes (referred to as candidate events). Fetal and maternal templates are generated automatically from the candidate events in the initialization period, and are used to classify the remaining candidate events based on certain similarity criteria. Once the fetal and maternal complexes are successfully detected and separated, a counting mechanism can be utilized to derive the corresponding heart rates. Computer simulations using real data demonstrate the effectiveness of the algorithm.
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