Multiscale analysis of heart rate, blood pressure and respiration time series

We present the multiscale entropy analysis of short term physiological time series of simultaneously acquired samples of heart rate, blood pressure and lung volume, from healthy subjects and from subjects with Chronic Heart Failure. Evaluating the complexity of signals at the multiple time scales inherent in physiologic dynamics, we find that healthy subjects show more complex time series at large time scales; on the other hand, at fast time scales, which are more influenced by respiration, the pathologic dynamics of blood pressure is the most random. These results robustly separate healthy and pathologic groups. We also propose a multiscale approach to evaluate interactions between time series, by performing a multivariate autoregressive modelling of the coarse grained time series: this analysis provides several new quantitative indicators which are statistically correlated with the pathology.