Variability of pressures and rates in the human cardiovascular system — Is it chaos or old fashioned noise?

Abstract

We discuss various traditional and new methods of modelling time series data to reveal dynamic characteristics. We consider cases in which measurements represent signals from a deterministic generator contaminated by additive noise or multiplicative noise. The properties of chaotic dynamics (nonlinear deterministic mechanisms) are also discussed. Fluctuations in cardiovascular data, as demonstrated in 24-hour ambulatory monitoring records of blood pressures, heart rate and core temperature, are then examined from these various perspectives, including spectral analysis. The pointwise correlation dimension calculated on R-R intervals on the 24-hour electrocardiogram (Holter record) is shown to reveal variations in physiological state that cannot be seen as clearly by spectral analysis. We conclude that both periodic models (simple systems) and chaotic models (complex systems) are useful in that different groups of subjects can be compared by either analysis. Neither model by itself, using standard algorithms, has the capability of identifying the mechanism actually generating the time history. Thus, we answer the question posed in the title of this paper as follows: It is difficult to decide on the basis of models of data only.