Linguistic analysis of the arterial pressure signals using frequency and rank order statistics

We introduce a quantitative metric to define distances among symbolic sequences. In application to the amplitude time series of arterial pressure signals, this approach provides new quantitative information that is not measured by conventional heart rate variability techniques. Complex physiologic signals may carry unique dynamical signatures that are related to their underlying mechanisms. We present a method based on rank order statistics of symbolic sequences to investigate the profile of different types of physiologic dynamics. We apply this method to amplitude of arterial pressure signals fluctuations. The method robustly discriminates patterns generated from healthy and pathologic states, as well as aging.