Dirichlet Distribution as a Model for Evaluation of the Condition of Adaptive Regulatory Systems in Human Organism in Heart Rate Variability Analysis

Search for methods of quick human organism condition estimation, early disease and pathology detection including...


Introduction
Search for methods of quick human organism condition estimation, early disease and pathology detection including preclinical and premorbid stages is still a challenge for the health care service, in particular, in relation to medical and demographic processes including population ageing which is apparent in most developed countries [1]. In preventive medicine in addition to information about disease occurrence and non-occurrence, it is important to be able to qualitatively and quantitatively evaluate the health condition of people from various age, social, occupational groups plus organism's functional reserves [2]. Nowadays a few methods are known which are based on heart rate variability analysis and indicate the state of regulatory systems of various levels [3,4]. However, each of the said methods has particular limitations which urge researchers to continue searches in the field. The problem articulated at the dawn of the method advent, namely investigation and evaluation human organism's adaptation processes [5] which might be consistent with aims of physiological studies remains urgent.
The problem is also important in many application aspects, in particular, for prompt control of patients' state in treatment and rehabilitation processes, and timely diagnostics of disease danger and prevention of related complications. In other words, the information to be acquired may be used for treatment and rehabilitation control, and primary, secondary, and tertiary disease prevention. The purpose of this paper is to examine the capability of the evaluation method for state of adaptive regulatory systems in heart rate variability analysis which is based on the statistical Dirichlet distribution model.

Materials and Study Methods
To evaluate physiological capability of the method we examined a few groups of patients having cerebrovascular pathology and generally healthy people of various ages. We studied: 68 patients The cardiointervalograms were constructed using Poly-Spectrum-Rhythm software and analyzed in a PC using RR Viewer. When developing the method we assumed that regulation system of blood circulation comprises a multi-circuit hierarchically self-   [6,7]. The function of the Dirichlet distribution which is defined on a k-dimensional simplex is equal to (1).
The model agrees with the formal connective between equilibrium thermodynamics and non-equilibrium thermodynamics and is consistent with main provisions of the dissipative structures theory proposed by I. Prigogine, the Nobel Prize winner [8].
Dirichlet distribution entropy can be represented as a sum (2).

Sch J Psychol & Behav Sci
452 group in SANSC indicator with significance value of α<0.01 and SNC indicator with significance value of α<0.1. It is indicative of informative value of statistic heart rate variability indicators (5)(6)(7)(8) which significantly describe the organism's functional condition and may be independent variables if disease severity level.
Significant distinction between "healthy people aged 30 to 62" and "encephalopathy" has not been found in any indicators.
The last-mentioned may be explained by undiagnosed preclinical (premorbid) stages of circulatory encephalopathy in a portion of conditionally healthy patients. The results we obtained prove the original concept of reduction of human organism's adaptive capability when diseases occur. We observe a steady tendency for SANSC adaptation factor to decrease which is governed by disease severity. Besides, contribution of autonomic nervous system elements to the self-organization process drops with disease severity while effect of humoral channel control rises.

Summary
The investigation we carried out has shown that informational and statistical heart rate variability analysis data sufficiently indicate the state of homeostasis of cardiac function control systems both for normal condition and pathology. This fact may be essential in studies of organism functions regulation processes, makes it possible to get the idea about organism's homeostatic opportunities and numerically evaluate them. The method we propose may be used for treatment and rehabilitation monitoring as well as primary, secondary and tertiary disease prevention.