Symbolic transformations of heart rate variability preserve information about cardiac autonomic control

Traditional measures of heart rate variability (HRV) in the time or frequency domain (e.g. standard deviation of normal-to-normal intervals, SDNN, or the high frequency component of spectral analysis, HF) may be used to track vagal and sympathetic modulation directed to the sinus node. In this study, we assess the ability of symbolic analysis to monitor cardiac autonomic regulation during two autonomic challenges (phenylephrine and nitroprusside; low and high dose of atropine). To assess the effect of the coarse graining procedure, symbolic series obtained from four different transformations over the original series and the series of successive differences of the original values. The analysis focused on patterns of length 3 and exploited a redundancy reduction strategy to group patterns into a small number of families. It turns out that each symbolic series created by the four transformations still contained sufficient dynamical features to quantify differences of cardiovascular changes during the pharmacological challenges. The symbolic series created by transformations of the beat-to-beat interview, i.e RR interval series, showed that patterns without variations (0V) appear more often during a high dose of atropine compared to rest or to a low dose of atropine. Furthermore, patterns with two unlike variations (2UV) appear more often during a low dose of atropine and less often during a high dose of atropine. Differences of nitroprusside and phenylephrine could also be assessed by patterns with these variations. In conclusion, the changes of cardiovascular regulation during pharmacological challenges can be assessed by the analysis of symbolic dynamics derived from the RR interval series independently of the specific symbolic transformation.