Andreotti Fernando, Behar Joachim, Zaunseder Sebastian, Oster Julien, Clifford Gari D
Institute of Biomedical Engineering, Faculty of Electrical and Computer Engineering, Technische Universität Dresden, Dresden, Germany. Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Physiol Meas. 2016 May;37(5):627-48. doi: 10.1088/0967-3334/37/5/627. Epub 2016 Apr 12.
Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be avoided. Data, extraction algorithms and evaluation routines were released as part of the fecgsyn toolbox on Physionet under an GNU GPL open-source license. This contribution provides a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms.
在过去几十年里，已经发表了许多关于从腹部记录中提取无创胎儿心电图（NI-FECG）的研究。这些研究大多声称在检测胎儿QRS（FQRS）复合波的位置方面取得了优异的成果。一小部分作者研究了从NI-FECG中提取形态学特征。然而，由于可用的公共数据库短缺、所采用的性能测量方法种类繁多以及缺乏开源参考算法，大多数研究成果无法得到有意义的评估。本文试图通过提出一种用于压力测试NI-FECG算法的标准化方法来解决这些问题，该方法包括绝对数据以及提取和评估程序。为此，创建了一个包含大量逼真人工信号的数据库，总计145.8小时的多通道数据和超过一百万个FQRS复合波。该数据集的一个重要特征是包含了几个对评估提取程序至关重要的非平稳事件（如胎儿运动、子宫收缩和心率波动）。为了展示我们的测试方法，对三类NI-FECG提取算法进行了评估：盲源分离（BSS）、模板减法（TS）和自适应方法（AM）。进行了实验，以在人工数据库上对八种NI-FECG提取算法的性能进行基准测试，重点关注：FQRS检测和形态分析（胎儿QT和T/QRS比值）。每组中表现最佳的方法的总体中位数FQRS检测准确率（即考虑所有非平稳事件），BSS为99.9%，AM为97.9%，TS为96.0%。结果表明，FQRS检测和形态学参数都严重依赖于提取技术和信噪比。特别是，研究表明应避免在使用BSS技术后获得的源域中对它们进行评估。数据、提取算法和评估程序作为fecgsyn工具箱的一部分，在GNU GPL开源许可下发布于Physionet上。本文为NI-FECG提取算法的基准测试和监管测试提供了一个标准框架。
