Based on the largest data set ever available for analysis of heart rate variability (HRV) variables, in healthy individuals, it was possible to determine the evolutionary behavior of three representative components of parasympathetic nervous system function (RMSSD, PNN50, and HF ms2), in different age groups of the life cycle: newborns, children and adolescents, young adults, and, finally, middle-aged adults. A near-parabolic and nonsynchronous behavior was observed among the different variables evaluated, with low values at first, then progressive elevation, and later fall, approximating the values of the newborns to the values of middle-aged adults and suggesting that the autonomic nervous system, at least relatively to its parasympathetic component, undergoes a growing maturation that is completed in the young adult and later suffers a progressive degeneration, completing the life cycle. This fact should be considered when comparing the analysis between healthy individuals and those with different states of pathological impairment.
Part of the book: Autonomic Nervous System Monitoring
Many variables have been used as homeostatic level markers. Heart Rate Variability (HRV) has been frequently cited as an indicator of homeostatic status. Low levels of HRV are associated with aging, disease, or increased risk of death. We present a study based on more than 10.5 million data collected from the literature, associating the degree of global clinical impairment of individuals, with their respective HRV data, seeking to establish a classification of Homeostatic Levels. Three specific variables were evaluated: heart rate (HR), the root-mean-square of successive differences between adjacent normal RR intervals in a time interval (RMSSD) and the HF band (HF ms2). It was possible to detect significant differences between the 83,927 data from healthy individuals and the 382,039 data from individuals with significant homeostatic impairment. It was demonstrated that the RMSSD is very sensitive to the worst homeostatic state, presenting a behavior independent of age and that the values found in the general population do not match the values of apparently healthy individuals. An alphanumeric classification of the homeostatic level in a three-level architecture was proposed, with three stages for each level, which may be extremely useful in prognostic assessment and decision-making about individual people.
Part of the book: Autonomic Nervous System
Heart Rate Variability (HRV) has been frequently cited as an indicator of homeostatic status. Low levels of HRV are associated with aging, disease, or increased risk of death. The authors based this chapter on an alphanumerical classification for the levels of homeostasis, structured on three linear variables (Heart Rate, RMSSD, and HF ms2) by analyzing a bigdata with more than 30 million pieces of data collected from literature. It was possible to confirm the clinical validity of this alphanumeric classification. It has been mentioned that HRV analysis in time and frequency domains are often not sufficient to characterize the complex dynamics of the heartbeat. Thus, the primary objective of this study was to verify whether or not there are correlations between the variables of the non-linear domain with variables and indices of the linear domain and also with the homeostatic level of individuals. It was found, contrary to expectations, that the variables ApEn, SampEntr and DFA α1 were not useful in characterizing the homeostatic level, since they do not differentiate between healthy and highly compromised individuals. Regarding the parasympathetic, sympathetic and stress indexes, only DFA a1 detected a correlation with the sympathetic index and the stress index.
Part of the book: Recent Advances in Homeostasis
The Gini Coefficient (GC) is a statistical tool widely used in Economics to quantify the degree of variation of values belonging to a group, ranging from zero to one. The closer to zero, the less unequal the country. We proposed to evaluate GC in the analysis of Heart Rate Variability in different groups of individuals hypothesizing that groups with more similar conditions and better stationarity (healthy individuals) should be the groups with lower differences among them and among the aged, diseased, or premature individuals. Time series of normal RR intervals were analyzed in eight groups of individuals: premature (G1) or healthy newborns (G2), healthy children (G3), healthy young adults (G4), elderly adults (G5), patients with chronic liver (G6) or kidney disease (G7) and individuals with a state of brain death or who died in the short term after the initial evaluation (G8). GC distinguished the less unequal groups (G2, G3 and G4) from all other groups. Was identified, graphically, a parabolic behavior with near similarity among equivalent homeostatic levels. GC is a useful tool for characterizing the stationarity and the homeostatic level of clinical groups (by lower GC values) and to interpret more adequately the results.
Part of the book: Time Series Analysis - Recent Advances, New Perspectives and Applications [Working title]