Entropy, entropy rate, and pattern classification as tools to typify complexity in short heart period variability series

An integrated approach to the complexity analysis of short heart period var iability series (300 cardiac beats) is proposed and applied to healthy subj ects during the sympathetic activation induced by head-up tilt and during t he driving action produced by controlled respiration (10, 15, and 20 breath s/min, CR10, CR15, and CR20 respectively). The approach relies on: 1) the C alculation of Shannon entropy (SE) of the distribution of patterns lasting three beats; 2) the calculation of a regularity index based on an entropy r ate (i.e., the conditional entropy); 3) the classification of frequent dete rministic patterns (FDPs) lasting three beats. A redundancy reduction crite rion is proposed to group FDPs in four categories according to the number a nd type or of heart period changes: a) no variation (0V); b) one variation (1V); and c) two like variations (2LV); 4) two unlike variations (2UV). We found that: 1) the SE decreased during tilt due to the increased percentage of missing patterns; 2) the regularity index increased during tilt and CR1 0 as patterns followed each other according to a more repetitive scheme; an d 3) during CR10, SE and regularity index were not redundant as the regular ity index significantly decreased while SE remained unchanged. Concerning p attern analysis we found that: a) at rest mainly three classes (0V, 1V, and 2LV) were detected; b) 0V patterns were more likely during tilt; c) IV and 2LV patterns were more frequent during CR10; and d) 2UV patterns were more likely during CR20. The proposed approach based on quantification of compl exity allows a full characterization of heart period dynamics and the ident ification of experimental conditions known to differently perturb cardiovas cular regulation.