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对心电信号进行分析,是医学临床上检测和诊断心脏功能的重要手段。室性心动过速(VT)和心室纤颤(VF)是威胁人类生命的严重的心脏疾病。本文应用联合熵方法分析正常心跳信号(NSR)、VT和VF信号的动力学复杂性信息。将动力学符号统计理论以及替代数据的概念融入其中,通过计算原始时间序列和其替代时间序列之间的联合熵值,来量化序列的动力学复杂性。经过对实际心率数据的计算机分析,证明了联合熵方法的合理性。根据联合熵值的不同对NSR、VT和VF信号进行区分,取得了令人满意的效果。
The analysis of ECG signals is an important means of clinical testing and diagnosis of cardiac function in medicine. Ventricular tachycardia (VT) and ventricular fibrillation (VF) are serious heart diseases that threaten human life. In this paper, the joint entropy method is used to analyze the dynamics complexity information of normal heart beat signal (NSR), VT and VF signals. Kinetic symbolic statistics theory and the concept of alternative data are incorporated into it, and the kinetic complexity of the sequence is quantified by calculating the joint entropy between the original time series and their alternative time series. After the computer analysis of the actual heart rate data, the rationality of the joint entropy method is proved. The NSR, VT and VF signals are distinguished according to the joint entropy values, and the satisfactory results are obtained.