ECGdeli-An open source ECG delineation toolbox for MATLAB
ECGdeli-An open source ECG delineation toolbox for MATLAB
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DOI：
10.1016/j.softx.2020.100639
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发表时间：
2021-01-01
期刊：
影响因子：
3.4
通讯作者：
Loewe, Axel
中科院分区：
文献类型：
--
作者：
Pilia, Nicolas;Nagel, Claudia;Loewe, Axel
心电图（ECG）是一种标准的成本效益和非侵入性工具，用于早期检测各种心脏疾病。量化单个ECG波形的不同定时和幅度特征以及单个ECG波形之间的不同定时和幅度特征可以揭示关于心脏的潜在（异常）功能的重要信息。确定这些特征需要检测标记每个ECG波形（P波、QRS波群、T波）的开启和偏移以及峰值的基准点。手动设置这些点是耗时的，并且需要医生的专业知识。因此，开发了高度模块化的ECGdeli工具箱MATLAB，它能够过滤临床记录的12导联ECG信号并检测基准点，也称为描绘。它是少数几个提供P波、T波和QRS波群ECG描绘的开放工具箱之一。使用QT数据库对所提供的算法进行了评价，QT数据库是一个ECG数据库，包括105个信号，其中基准点由临床医生注释。对于P波和QRS波群标记，由边界检测算法设置的基准点与用作基础事实的临床注释之间的中值差小于4个样本（16 ms）。检测T波起始、峰值和偏移，中位差分别为5、2和7个样本。将结果与PhysioNet上提供的两种免费算法进行比较。我们的研究结果表明，ECGdeli可以可靠地检测P波，QRS波群和T波。因此，通过分析ECG信号可以有助于诊断特定的心脏疾病。由于ECGdeli是在GNU GPL v3下发布的，并且由于其模块化，它可以用于扩展现有算法或作为新算法的基准。(c)2020作者（S）由Elsevier B.V.发布。这是CC BY许可下的开放获取文章
The electrocardiogram (ECG) is a standard cost-efficient and non-invasive tool for the early detection of various cardiac diseases. Quantifying different timing and amplitude features of and in between the single ECG waveforms can reveal important information about the underlying (dys-)function of the heart. Determining these features requires the detection of fiducial points that mark the on- and offset as well as the peak of each ECG waveform (P wave, QRS complex, T wave). Manually setting these points is time-consuming and requires a physician's expert knowledge. Therefore, the highly modular ECGdeli toolbox for MATLAB was developed, which is capable of filtering clinically recorded 12-lead ECG signals and detecting the fiducial points, also called delineation. It is one of the few open toolboxes offering ECG delineation for P waves, T Waves and QRS complexes. The algorithms provided were evaluated with the QT database, an ECG database comprising 105 signals with fiducial points annotated by clinicians. The median difference between the fiducial points set by the boundary detection algorithm and the clinical annotations serving as a ground truth is less than 4 samples (16 ms) for the P wave and the QRS complex markers. The T wave onset, peak and offset were detected with a median difference of 5, 2 and 7 samples, respectively. Results were compared to two free algorithms available on PhysioNet. Our results show that ECGdeli can reliably detect P waves, QRS complexes and T waves. Thus, it can contribute to diagnose specific cardiac diseases by analyzing the ECG signal. As ECGdeli is published under GNU GPLv3 and thanks to its modularity, it can be used to extend existing algorithms or as a benchmark for new algorithms.(c) 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license