Complexity in Heart Rate Variability after Postural Sympathovagal Change by Sample, Fuzzy, and Distribution Entropy

Abstract

Distribution Entropy (DistEn) has been proposed to quantify the heart rate variability (HRV) complexity as an alternative to Sample (SampEn) or Fuzzy (FuzzyEn) entropies, which essentially measure the HRV randomness. We aim to evaluate if postural sympathovagal activations in healthy individuals induce changes in HRV complexity or randomness by jointly estimating DistEn, SampEn, and FuzzyEn. We compared the estimators on white, pink, and random noises, and on chaotic and periodic series. Then, we considered supine (Sup) and sitting (Sit) heart-rate recordings of 34 volunteers comparing SampEn, FuzzyEn, and DistEn between postures. Synthesized series highlighted the different nature of the estimators, being the highest entropy that of white noise for SampEn and FuzzyEn, that of the chaotic series for DistEn. SampEn and FuzzyEn of real heart rate series were greater in Sup, while DistEn did not differ between postures. Thus, the postural change does not change the HRV complexity as quantified by DistEn and DistEn is not an index of sympathovagal balance, unlike SampEn or FuzzyEn.