Makowiec Danuta, Struzik Zbigniew, Graff Beata, Wdowczyk-Szulc Joanna, Zarczynska-Buchnowiecka Marta, Gruchala Marcin, Rynkiewicz Andrzej
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:6127-30. doi: 10.1109/EMBC.2013.6610951.
Network models have been used to capture, represent and analyse characteristics of living organisms and general properties of complex systems. The use of network representations in the characterization of time series complexity is a relatively new but quickly developing branch of time series analysis. In particular, beat-to-beat heart rate variability can be mapped out in a network of RR-increments, which is a directed and weighted graph with vertices representing RR-increments and the edges of which correspond to subsequent increments. We evaluate entropy measures selected from these network representations in records of healthy subjects and heart transplant patients, and provide an interpretation of the results.
网络模型已被用于捕捉、表示和分析生物体的特征以及复杂系统的一般属性。在时间序列复杂性表征中使用网络表示是时间序列分析中一个相对较新但发展迅速的分支。特别是,逐搏心率变异性可以在RR间期增量网络中描绘出来,这是一个有向加权图,其顶点代表RR间期增量,边对应于后续增量。我们在健康受试者和心脏移植患者的记录中评估从这些网络表示中选择的熵度量,并对结果进行解释。