Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

Abstract

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for
the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded
associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-
term structural and functional changes.
Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while
evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.
Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During
the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in
the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval
and amplitude of ST segment taken from the V standard lead.
Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment
amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical
levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate
of the myocardium and reflected in the dynamics of all investigated interactions.
Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions
show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional
state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be
assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation
of the interactions of physiological signals by using time series analysis methods is suitable for the observation of
these processes and the functional state of the body.

Keywords: electrocardiogram, time series, functional state.