Sleep is a physiological process involving different biological systems, from molecular to organ level; its integrity is essential for maintaining health and homeostasis in human beings. Although in the past sleep has been considered a state of quiet, experimental and clinical evidences suggest a noteworthy activation of different biological systems during sleep. A key role is played by the autonomic nervous system (ANS), whose modulation regulates cardiovascular functions during sleep onset and different sleep stages. Therefore, an interest on the evaluation of autonomic cardiovascular control in health and disease is growing by means of linear and non-linear heart rate variability (HRV) analyses. The application of classical tools for ANS analysis, such as HRV during physiological sleep, showed that the rapid eye movement (REM) stage is characterized by a likely sympathetic predominance associated with a vagal withdrawal, while the opposite trend is observed during non-REM sleep. More recently, the use of non-linear tools, such as entropy-derived indices, have provided new insight on the cardiac autonomic regulation, revealing for instance changes in the cardiovascular complexity during REM sleep, supporting the hypothesis of a reduced capability of the cardiovascular system to deal with stress challenges. Interestingly, different HRV tools have been applied to characterize autonomic cardiac control in different pathological conditions, from neurological sleep disorders to sleep disordered breathing (SDB). In summary, linear and non-linear analysis of HRV are reliable approaches to assess changes of autonomic cardiac modulation during sleep both in health and diseases. The use of these tools could provide important information of clinical and prognostic relevance.

Two symbolic indexes, the percentage of sequences characterized by three heart periods with no significant variations (0V%) and that with two significant unlike variations (2UV%), have been found to reflect changes in sympathetic and vagal modulations, respectively. We tested the hypothesis that symbolic indexes may track the gradual shift of the cardiac autonomic modulation during an incremental head-up tilt test. Symbolic analysis was carried out over heart period variability series (250 cardiac beats) derived from ECG recordings during a graded head-up tilt test (0, 15, 30, 45, 60, 75, and 90°) in 17 healthy subjects. The percentage of subjects showing a significant linear correlation (Spearman rank-order correlation) with tilt angles was utilized to evaluate the performance of symbolic analysis. Spectral analysis was carried out for comparison over the same series. 0V% progressively increased with tilt angles, whereas 2UV% gradually decreased. The decline of 2UV% was greater than the increase of 0V% at low tilt angles. Linear correlation with tilt angles was exhibited in a greater percentage of subjects for 0V% and 2UV% than for any spectral index. Our findings suggest that symbolic analysis performed better than spectral analysis and, thus, is a suitable methodology for assessment of the subtle changes of cardiac autonomic modulation induced by a graded head-up tilt test. Moreover, symbolic analysis indicates that the changes of cardiac sympathetic and vagal modulations observed during this protocol were reciprocal but characterized by different absolute magnitudes.

We exploit time reversibility analysis, checking the invariance of statistical features of a series after time reversal, to detect temporal asymmetries of short-term heart period variability series. Reversibility indexes were extracted from 22 healthy fetuses between 16th to 40th wk of gestation and from 17 healthy humans (aged 21 to 54, median = 28) during graded head-up tilt with table inclination angles randomly selected inside the set {15, 30, 45, 60, 75, 90}. Irreversibility analysis showed that nonlinear dynamics observed in short-term heart period variability are mostly due to asymmetric patterns characterized by bradycardic runs shorter than tachycardic ones. These temporal asymmetries were 1) more likely over short temporal scales than over longer, dominant ones; 2) more frequent during the late period of pregnancy (from 25th to 40th week of gestation); 3) significantly present in healthy humans at rest in supine position; 4) more numerous during 75 and 90° head-up tilt. Results suggest that asymmetric patterns observable in short-term heart period variability might be the result of a fully developed autonomic regulation and that an important shift of the sympathovagal balance toward sympathetic predominance (and vagal withdrawal) can increase their presence.

Complexity (or its opposite, regularity) of heart period variability has been related to age and disease but never linked to a progressive shift of the sympathovagal balance. We compare several well established estimates of complexity of heart period variability based on entropy rates [i.e., approximate entropy (ApEn), sample entropy (SampEn), and correct conditional entropy (CCE)] during an experimental protocol known to produce a gradual shift of the sympathovagal balance toward sympathetic activation and vagal withdrawal (i.e., the graded head-up tilt test). Complexity analysis was carried out in 17 healthy subjects over short heart period variability series (∼250 cardiac beats) derived from ECG recordings during head-up tilt with table inclination randomly chosen inside the set {0, 15, 30, 45, 60, 75, 90}. We found that 1) ApEn does not change significantly during the protocol; 2) all indices measuring complexity based on entropy rates, including ad hoc corrections of the bias arising from their evaluation over short data sequences (i.e., corrected ApEn, SampEn, CCE), evidence a progressive decrease of complexity as a function of the tilt table inclination, thus indicating that complexity is under control of the autonomic nervous system; 3) corrected ApEn, SampEn, and CCE provide global indices that can be helpful to monitor sympathovagal balance.