ANALYSIS OF HRV SIGNALS BASED ON THE HIGH-ORDER COMPLEXITY MEASUREMENT
基于高阶复杂性测度的心率变异信号分析

The heart rate variability(HRV) reflects the synthetical function of the parasympathetic-sympathetic nerve to adjust and control the heart and blood system, and it is an important index to evaluate the function of the heart and blood system. The complexity is a valuable parameter representing the information contained in a time series, but the traditional algorithm of measure complexity is so rough that a lot of information contained in the time series will be lost, and this can be avoided by higher order complexity. Based on a simulation of Lorenz model, the all Kolmogorov complexity indexes of two groups of samples of 25 normal populations and 25 congestive heart failure patients were calculated and analyzed, and an important conclusion was given that the 5th order complexity was the best equal complexity index to represent the HRV.