Objective: Symbolic transformations of the cardiac interbeat interval series yield a coarse-grained description of the dynamical information of the underlying system and complement standard measures of heart rate variability. The most commonly utilized coarse graining procedures are strongly influenced by the presence of a few extreme values wasting precious symbols to code very unlikely values.
Approach: Here, we used a transformation procedure that ensured the appearance of each symbol with equal probability using a short alphabet, A 4 = {0, 1, 2, 3}, and a long alphabet, A 6 = {0, 1, 2, 3, 4, 5}. The procedure was applied to the cardiac interbeat interval series of 17 healthy subjects, obtained during graded head-up tilt tests at tilt table inclinations of 0°, 15°, 30°, 45°, 60°, 75°, 90°. The dynamics of the symbolic series was assessed by the rate of symbolic pattern categories. Symbolic patterns of length three were grouped according to the variations of the symbols in each pattern: no variation (0V%), one variation (1V%), two like variations (2LV%) and two unlike variations (2UV%) of the symbols.
Main results: As for the alphabet A 4, the linear regression analysis on tilt angle showed that 0V% increased with increasing tilt angle whereas 1V%, 2LV% and 2UV% decreased. As for the alphabet A 6, the categories 0V%, and 1V% increased with increasing tilt angle whereas 2LV% and 2UV% decreased.
Significance: The symbolic transformation ensuring a uniform distribution of the symbols is capable of reflecting changes in the cardiac autonomic nervous system during graded head-up tilt. This approach is more robust against outliers and data with skewed distributions compared to previously used symbolizations.