An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms

被引:118
|
作者
Andreotti, Fernando [1 ,2 ]
Behar, Joachim [3 ]
Zaunseder, Sebastian [1 ]
Oster, Julien [2 ]
Clifford, Gari D. [4 ,5 ,6 ]
机构
[1] Tech Univ Dresden, Fac Elect & Comp Engn, Inst Biomed Engn, D-01062 Dresden, Germany
[2] Univ Oxford, Dept Engn Sci, Inst Biomed Engn, Parks Rd, Oxford OX1 3PJ, England
[3] Technion Israel Inst Technol, Biomed Engn Fac, Haifa, Israel
[4] Emory Univ, Dept Biomed Informat, Atlanta, GA 30322 USA
[5] Emory Univ, Dept Biomed Engn, Atlanta, GA 30322 USA
[6] Georgia Inst Technol, Atlanta, GA 30332 USA
关键词
foetal ECG (FECG); foetal QRS (FQRS); morphological analysis; benchmark; blind source separation (BSS); template subtraction; adaptive filtering; INDEPENDENT COMPONENT ANALYSIS; BLIND SOURCE SEPARATION; HEART-RATE-VARIABILITY; ELECTROCARDIOGRAM EXTRACTION; MODEL; RECORDINGS; PREDICTION; MIXTURES; SIGNALS; NOISY;
D O I
10.1088/0967-3334/37/5/627
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
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.
引用
收藏
页码:627 / 648
页数:22
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