基于排列熵的心电信号非线性分析

排列熵是一种基于复杂性量度的非线性动力学参数,能够快速、有效地反映系统的特征。目前在心电信号检测研究中还少有此类方法的应用,通过对算法进行研究,并应用于心室病症的检测中,利用MIT—BIH数据库,对心室病症心电信号的发病时段进行排列熵值的计算,实验得出,熵值对病症发作时段的反映灵敏,在心室纤颤、室性心动过速等病症上的检测准确率较高。因此得到结论,排列熵是一个早期检测病症的灵敏参数,可以作为临床诊断的有效依据。

Nonlinear Analysis of ECG Signal Based on Permutation Entropy

As a nonlinear dynamic parameter based on complexity measurement, permutation entropy （PE） can reflect the characteristics of the system quickly and effectively. PE method is seldom used in ECG detection and research. The PE value for the morbidity time intervals in the electroeardiosignal of ventricular disease is calculated with the MIT-BIH database after the research of the algorithm. The experiment shows that the PE value has sensitive reflection to the morbidity time intervals in the electrocardiosignal of ventricular disease, and the detection accuracy rate is high for the ventricular fibrillation, ventricular tacb.yeardia and other diseases. The research proves that PE is a sensitive parameters which can he used in clinical diagnosis.