Amplitude symbolic analysis: a tool for the evaluation of the autonomic function complementary to traditional symbolic approach

Symbolic analysis (SA) infers cardiac control from spontaneous stationary sequences of heart period (HP) by estimating the probability of symbolic pattern classes. Unfortunately, SA does not assess the fraction of HP variability associated with symbolic pattern families. This study proposes amplitude SA (ASA) accounting for absolute changes between consecutive HPs. ASA leverages uniform 6-bin quantization to symbolize HP, the delay embedding procedure to form length-3 symbolic patterns and a traditional strategy to group symbolic patterns into four classes families according to number and sign of variations between adjacent symbols. ASA computes the fraction of variance associated with symbolic pattern classes. ASA was applied to HP variability derived from: 1) healthy subjects during pharmacological challenges (n = 9; age: 25-46 yrs, 9 males); 2) healthy subjects during graded postural stimuli (n = 19; age: 21-48 yrs, 8 males); 3) Parkinson disease (PD) patients (n = 12; age: 55-79 yrs, 8 males) and matched healthy controls (n = 12; age: 58-72 yrs, 7 males). We computed both global and local ASA markers and we compared them with SA indexes. Over stationary HP series we found that: i) ASA provides a general method to decompose HP variance according to symbolic pattern classes; ii) ASA is useful to describe cardiac control; iii) ASA indexes are complementary to SA markers; iv) ASA emphasizes the link of HP variability markers expressed in absolute units with vagal control; v) global and local ASA approaches provide similar information. SA and ASA should be utilized concomitantly for a deeper characterization of cardiac control from spontaneous HP fluctuations.