Zhou Shijie, Zhang Zichen, Gu Jason
Department of Electrical and Computer Engineering, Dalhousie University, Halifax, NS B3J 2X4,
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:2716-9. doi: 10.1109/IEMBS.2011.6090745.
Lempel-Ziv (LZ) complexity measure has been applied to classify ventricular tachycardia (VT) and ventricular fibrillation (VF). The coarse-graining process plays a crucial role in the LZ complexity measure analysis, which directly affects the separating performance of VT and VF in ECG signal analysis. The question of different coarse-graining approaches interpretability in ECG signal analysis and their influence on the performance of ECG classification have not yet been previously addressed in the literature. In this paper, we present four coarse-graining process approaches, K-Means, Mean, Median and Mid-point. Our test shows that K-Means algorithm is superior to the other three approaches in VT and VF separation rate, Particularly, optimum performance is achieved at a 8-second window length.
莱姆佩尔-齐夫（LZ）复杂度度量已被应用于室性心动过速（VT）和心室颤动（VF）的分类。粗粒化过程在LZ复杂度度量分析中起着关键作用，它直接影响心电图（ECG）信号分析中VT和VF的分离性能。不同粗粒化方法在ECG信号分析中的可解释性问题及其对ECG分类性能的影响在以前的文献中尚未得到解决。在本文中，我们提出了四种粗粒化过程方法，即K均值、均值、中位数和中点法。我们的测试表明，K均值算法在VT和VF分离率方面优于其他三种方法，特别是在8秒的窗口长度下可实现最佳性能。
