摘要
It is difficult to establish the process of chaos in time series from cardiac dynamics. The output from such a system is probably the result of both its internal dynamics, and the input to the system from its surroundings. We present an optimization algorithm to find a time series that is as close as possible to the heart rate series subject to the constraint that it is deterministic with respect to some dynamics. The algorithm is tested by some famous forced dynamical systems, and applied to heart rate data. We find that the deterministic components of heart rate variability are chaotic.
心脏动力系统可能是其内在动力学和外部环境影响的混合体，因此从心率变异信号中确定混沌现象非常困难．本文提出一种优化方法，获得一组由某种动力系统产生的时间序列，并使该序列与原始信号尽可能接近．对动力噪声干扰混沌模型进行了检验后，应用于心率变异信号分析时发现了正的最大Ｌｙａｐｕｎｏｖ
