瞬时P波和t波检测:三种心电基点检测算法的评估

Heike Leutheuser, Stefan Gradl, L. Anneken, M. Arnold, N. Lang, S. Achenbach, B. Eskofier
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引用次数: 12

摘要

心律失常检测算法要求准确、即时地检测心电信号中的基点。这些基点(qrs复合体,P波和t波)对应于不同的心脏收缩期。不同基点检测算法的性能评估需要包含参考注释的大型数据库的存在。直到去年,P- wave和T-wave注释还只能用于QT DB。Elgendi等人解决了这个问题,他们为MIT-BIH心律失常数据库提供了P波和t波注释。文献中存在各种ECG基点检测算法,然而,据作者所知,我们无法识别任何用于瞬时P波和t波检测的单导联算法。在这项工作中,我们提出了三种P波和t波检测算法:一种使用能够检测P波和t波的线拟合的QRS检测修订版,一种基于小波的心电描绘算法的快速版本,以及一种快速朴素基点检测算法。快速天真基准点检测算法对两种db的灵敏度均为73.0% (p波检测,误差范围为±40 ms) ~ 89.4% (t波检测,误差范围为±80 ms)。由于该算法在每个搜索窗口中检测到一个波事件,因此必须研究这对心律失常检测算法的影响。参考Matlab实现可以下载,以鼓励开发高精度和自动化的心电处理算法,以便在日常生活中使用移动计算机进行集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Instantaneous P- and T-wave detection: Assessment of three ECG fiducial points detection algorithms
Arrhythmia detection algorithms require the exact and instantaneous detection of fiducial points in the ECG signal. These fiducial points (QRS-complex, P- and T-wave) correspond to distinct cardiac contraction phases. The performance evaluation of different fiducial points detection algorithms require the existence of large databases (DBs) encompassing reference annotations. Up to last year, P- and T-wave annotations were only available for the QT DB. This was addressed by Elgendi et al. who provided P- and T-wave annotations to the MIT-BIH arrhythmia DB. A variety of ECG fiducial points detection algorithms exists in literature, whereas, to the best knowledge of the authors, we could not identify any single-lead algorithm ready for instantaneous P- and T-wave detection. In this work, we present three P- and T-wave detection algorithms: a revised version for QRS detection using line fitting capable to detect P- and T-wave, an expeditious version of a wavelet based ECG delineation algorithm, and a fast naive fiducial points detection algorithm. The fast naive fiducial points detection algorithm performed best on both DBs with sensitivities ranging from 73.0% (P-wave detection, error interval of ± 40 ms) to 89.4% (T-wave detection, error interval of ± 80 ms). As this algorithm detects a wave event in every search window, it has to be investigated how this affects arrhythmia detection algorithms. The reference Matlab implementations are available for download to encourage the development of high-accurate and automated ECG processing algorithms for the integration in daily life using mobile computers.
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