提出了一种新的时间序列转换成网络的方法,从而可以通过网络拓扑统特征来刻画时间序列。将该方法应用于心室纤颤的检测中,发现健康个体与室颤病人相应网络非常明显的不同,将网络的聚类系数与同配系数作为联合指标可以区分两者。此外,还将该算法应用于HRV分析,结果表明,算法能够区分不同病态下的心跳间隔信号。 A new method to convert time series to network is proposed, which can characterize the time series through the features of network topology. The method is applied to the detection of ventricular fibrillation and found that the corresponding network of healthy individuals and patients with ventricular fibrillation is very different, the clustering coefficient of the network with the same coefficient as a joint indicator can distinguish between the two. In addition, the algorithm is also applied to HRV analysis, the results show that the algorithm can distinguish between different pathological heartbeat interval signal.