Psychological correlates of athletic success in athletes training
Sport GDV Bioelectrography Research
Psychophysiological Correlates of Athletic Success in Athletes Training for the Olympics
P. V. Bundzen†, K. G. Korotkov, A. K. Korotkova, V. A. Mukhin, and N. S. Priyatkin
St. Petersburg Institute of Physical Training, St. Petersburg, Russia e-mail: gdv@korotkov.org
Received March 31, 2004
Abstract—Long-term studies related to comprehensive analysis of psychophysiological correlates of the ath- letic potential were performed on the basis of innovative technologies of molecular genetic and biological energy analyses using modern automated software–hardware complexes. The results were used to select indices for personalized diagnosis of the athletic potential, to analyze it comparatively at the team level, and to calculate an athletic rating correlating with athletic success. These indices make it possible to detect preclinical health disturbances, development of energy deficit, and overtraining. The approaches may be used to analyze the gen- eral well-being of a population.
† Studies of athletic success have shown the impor- tance of an optimal combination of the following fac- tors in various sports: (1) the general psychoemotional status of an athlete, with a predominance of activity, resoluteness, and ability to work in a team (for team sports); (2) a high tone of the cardiovascular system and oxygen uptake; (3) a correspondence of the muscular structure and activity to the sports in which the athlete engages; and (4) a high level of physical training [1].
At the same time, competitive sports performance with a high level of success is characterized by some factors that distinguish it from simple physical training: (1) necessity of maximum realization of accumulated psychophysiological resources in contests and their purposeful use throughout the year in accordance with the contest schedule and (2) efficient use of relaxation and rehabilitation periods between contests to restore the spent resources.
It is important to take into account the necessity to safeguard the health of athletes and prevent overtrain- ing and overstrain, which lead to failures and injuries.
It is the task of coaches, sports physicians, and psy- chologists to take into account these factors and their interrelations and synergy in practical work related to athletics. Therefore, it is important to elucidate the parameters of the psychophysiological functional state of an athlete on the whole and develop equipment and methods for prompt evaluation and monitoring of ath- letes’ state during training and contests. The main requirements for these methods are that they be (1) informative with respect to the features of athletic
† Deceased.
activity; (2) objective and independent from the opera- tor and the conditions of data collection; (3) capable of allowing simple and rapid measurements and analysis; (4) usable in a wide range of conditions, including those of a contest; (5) reliable as concerns the storage of large data files; (6) accessible to nonprofessional operators, including athletes (self-monitoring); and (7) capable of providing graphic and understandable infor- mation.
It is evident that only modern computerized com- plexes meet these requirements.
Under the guidance of Prof. P.V. Bundzen, research- ers of the St. Petersburg Institute of Physical Training and the University of Information Technologies, Mechanics, and Optics (St. Petersburg) developed from 1998 to 2003 systems for comprehensive diagnosis of athletic potential. The systems include innovative tech- nologies of molecular genetic and biological energy analyses that are based on modern automated software– hardware complexes.
METHODS
The set of parameters under study included six blocks that make it possible to evaluate the psycho- physiological potential (the level of psychophysiologi- cal reserves) of an athlete (Fig. 1): (1) a valeometric block for evaluation of health quality and exercise per- formance; (2) a block for evaluation of the psychoemo- tional status by the depth and direction of changes in it; (3) a block for evaluation of autonomic and humoral control on the basis of the heart rate variability method; (4) a block for evaluation of the state of energy homeostasis on the basis of gas discharge visualization (GDV) bioelectrography (on the scale of energy excess–nor- mal level–energy deficit); (5) a block for evaluation of genetic predisposition for physical activity; and (6) a block for generation of conclusions on the basis of computerized systems of artificial intelligence.
The valeometric block included the following sub- systems: (1) personal data about the subject; (2) mor- phofunctional indices (body length, body mass, blood pressure, and heart rate at rest and during exercise); (3) current psychosomatic complaints; and (4) genetically determined and acquired risk factors.
Exercise performance was evaluated with a Quinton treadmill (United States) in the following velocity regimes: 6 km/h at the first level, 9 km/h at the second, and 12 km/h at the third. The slope was 5% and the duration of each level, 3 min. Then the angle increased to 12.5% with a duration of 1 min at each level. At the third level, where the velocity was 12 km/h, the athletes ran to capacity. The heart rate was continuously moni- tored using a Polar Electro system; external respiration was controlled every 3 min using a Beckman gas ana- lyzer.
The psychoemotional status was evaluated using a Russian version of the POMS test [2], by measuring six indices: (1) anxiety (T); (2) depression (D); (3) aggres-
siveness (A); (4) activity (V); (5) fatigue (F); and (6) confusion (C).
Heart rate variability was assayed using Polar Elec- tro OY and Heart Tuner cardiomonitors when a subject was in the supine position at relative physiological rest. The results were processed mathematically using the Polar Precision Performance computer program. We calculated the parameters of time area, scattergrams, and histograms [3]. Histograms were plotted with an interval of 0.05 s. In addition, absolute and relative powers of the spectrum of periodic fluctuations of the heart rate were evaluated in the standard frequency ranges: ≤0.04 (VLF), 0.04–0.1 (LF), and 0.1–0.4 Hz (HF). Spectrum amplitudes were evaluated at all fre- quencies with a step of 0.01 Hz.
GDV bioelectrography is based on recording opto- electron emission of a biological object upon stimula- tion with short (3–5 μs) electromagnetic pulses [4]. The method makes it possible to record and quantify lumi- nescence near the surface of the object in a high-voltage electromagnetic field (EMF) (Fig. 2). The method is used to study stimulated emission of photons, elec- trons, and other particles of the object exposed to an EMF or a gas discharge. Biological emission strength- ens in a gas discharge and is transformed into a digital code by a video transformation system, digitalized by a computer, and imaged as a GDV-gram. The GDV-gram
2005-Sport_Physiol-Chelov_E