Lupine Publishers | Scholarly Journal Of Psychology And Behavioral Sciences
Introduction
Search for methods of quick human
organism condition estimation, early disease and pathology detection including
pre-clinical 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 (36 female and 32 male) aged 32 to 65
having circulatory system diseases and diagnosed with encephalopathy; 38
patients (20 female and 18 male) aged 32 to 65 having circulatory system
diseases and diagnosed with cerebrovascular accident; 38 generally healthy
patients (21 female and 17 male) aged 32 to 60 having no cerebrovascular
pathology symptoms. The reference group included 23 generally healthy patients
under investigation (14 female and 9 male) aged 18 to 23. All people under test
were investigated using standard method: electrocardiograms (ECG) were produced
for 5 minutes with people at rest in prone position. The electrocardiograms
were obtained using Poly-Spectrum-8 electrocardiograph (Neurosoft LLC, City of
Ivanovo). 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-organizing system exhibiting non-linearity, sophistication
and open nature while dissipative processes including friction, diffusion and
dissipation construct ties between components and elements of the said system
and generally progressive motion thereof. The complex nature of interaction
between elements of the nervous, hormonal, and humoral regulation system and
effect on of the state thereof of many external poorly-controlled factors
result in that the processes which define heart rate variability exhibit
accidental nature and may be represented by a statistical model (statistically)
in the form of probability distributions. We proposed to use Dirichlet
distribution as the said model. As a model the distribution is informatively
equivalent to the object of which state displays the outcome of joint
occurrence of n-1 independent processes xi occurring at rates (intensities) of vi and opposite in essence to the
process occurring at the rate of vn [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).
corresponds
to the entropic flux accountable for the interaction processes with
environment. At n ≥ 3 entropy (4) may be both positive and negative which in
Dirichlet distribution model terms makes it possible to regard He(an) < 0 as one of the selforganization conditions.
The state of homeostasis in control of the autonomic nervous system of cardiac
function was assessed [9] by the self-organization indicator value (factor) in
control of the autonomic nervous system of cardiac function (Self-organization
of Autonomic Nervous System Control - SANSC) expressed by equation (5):
where
DiQ
− is the number of Dirichlet models
of i-dimensionality with a negative outer entropy value found in temporal
series of RR intervals within the investigation period, and DiQ + is
the number of Dirichlet models of i-dimensionality with a positive outer entropy
value found in temporal series of RR intervals within the investigation period.
Contribution made by individual elements of the autonomic nervous system to the
self-organization of vegetative regulation was assessed by the quantity of
Dirichlet models found in the temporal series of RR intervals within the
investigation period: of 2-4 (parasympathetic nervous system) or 5-7
(sympathetic nervous system) dimensionality with negative outer entropy.
Self-organization factor of cardiac function control by the parasympathetic
nervous system (Self-organization of Parasympathetic Nervous System Control -
SPNSC) as opposed to [9] is calculated from the formula (6).
Self-organization factor of cardiac
function control by the sympathetic nervous system (Self-organization of
Sympathetic Nervous System Control - SSNSC) is calculated from the formula (7).
Contribution to cardiac function control self-organization of humoral processes was assessed by the factor value of humoral cardiac function control self-organization (Self-organization of Humoral Control - SHC) (8).
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.
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