DYNAMICS OF SPECTRAL INDEXES OF HEART VARIABILITY RATE OF THE STUDENTS WITH DIFFERENT CHARACTER OF THE EDUCATIONAL LOADING
Ternopil V. Hnatyuk National Pedagogical University
It has been analyzed in the article the change of spectral
parameters of heart rate variability of the students of various
disciplines influenced by conditions of educational and practical
activities. It has been established that during training for
women of all groups the studied parameters were reduced, and
the students of «Physical culture» value LF increased almost
in 2 times (P≤0,05) in parallel with a decrease of VLF (of 902
[497; 1417] to 516 [401; 723] square milliseconds P≤0,05).
During the internship in students of «Foreign Languages»
significantly increased rate of vegetative balance LF/HF (from
1,47 [0,88; 1,80] to 1,63 [1,18; 3,15] standard units, P≤ 0.05)
and all the studied parameters tended to increase (P≥0,05). The
growth of total power of spectrum (1969 [1298, 2398] to 3273
[1874; 4568] square milliseconds P≤0,05) in women specialty
«Chemistry and Biology» testified to the increased activity of
independent regulation circuit. In the students’ «Physics and
Mathematics» and «Physical Education» downward trend
indicators had HF, VLF, TP and to increase – LF and LF /
HF (P≥0,05). Changes of spectral indices point to strengthen
sympathykotonic impacts and reduction of adaptive capacity in
women «Physical Education» experiencing psycho-emotional
tension combined with mental and physical load.
heart variability rate, spectral indexes, vegetative nervous system, sympathetic and parasympathetic links of regulation, students of pedagogical higher educational establishment
- Guazzi M, Faggiano P, Mureddu GF, 2014. Worksite health and wellness in the European union. Prog Cardiovasc Dis. Mar-Apr. 56(5): 508–514.
- Sorokin AV, 2007. Dr Med Sci. Abstract dis. Chelyabinsk, 46 p. [Russian].
- Shook NJ, Fazio RH, Vasey MW, 2007. Negativity bias in attitude learning: a possible indicator of vulnerability to emotional disorders? J Behav Ther Exp Psychiatry. 38: 144-55.
- Bernada VV, 2008. Kand. biol. sci. abstrat dis. Kyiv, 20 p. [Ukrainian].
- Bulateckij SV. Prognostic significance of heart variability rate at the psychoemotional trial in groups with different success of vocational training. In: Actual issues of Clinical and Experimental Pathology. Ryazan: RyazGMU, 2005, P. 20-7. [Russian].
- Suls J, 2013. Anger and the heart: perspectives on cardiac risk, mechanisms and interventions. Prog Cardiovasc Dis. May-Jun, 55(6):538-47.
- Weber CS, Thayer JF, Rudat M, Wirtz PH, 2010. Low vagal tone is associated with impaired post stress recovery of cardiovascular, endocrine, and immune markers. Eur J Appl Physiol. 109: 201-11.
- Baevskij PM, Ivanov GG. Heart variability rate: theoretical aspects and clinical applications (Eds SV Grachev, GG Ivanov, AL Syrkin). Moscow: Tehnosfera, 2007, P. 473-496
- Thayer JF, Ahs F, Fredrikson M, Sollers JJ, Wager TD, 2012. A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neurosci and Biobehavioral Rev. 36: 747-56.
- Val'kova NJu, 2007. Dr. biol. sci. abstract dis. Arkhangelsk, 40 p. [Russian].
- Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart Rate Variability. Standards of measurements, Physiological Interpretation, and Clinical Use. Circulation, 1996. 93: 1043-65.
- Quintana DS, Guastella AJ, Outhred T, Hickie IB, Kemp AH, 2012. Heart rate variability predicts emotion recognition: Direct evidence for a relationship between the autonomic nervous system and social cognition. International J Psychophysiol. 86(2): 168-72.
- Osadchaja EA, 2004. Kand Biol Sci. Dis. Orel, 173 p. [Russian]
- Peacock J, Whang W, 2013. Psychological distress and arrhythmia: risk prediction and potential modifiers. Prog Cardiovasc Dis. May-Jun, 55(6): 582-89.
- Glushko AN, 2006. Dr. psychol sci abstract dis. Moscow, 44 p. [Russian].
- Romanova ES, 2004. 99 popular professions. Psychological analysis and professiogram. SPb.: Piter, 464 p. [Russian].
- The system of the complex by computer studies of the functional state of the human body «Omega-M», 2001. SPb: Scientific research. Laboratory «Dynamics», 67 p. [Russian].
- Buccelletti F. Maria GB, Gilardi E, Viore F, Calcinaro S, 2012. Computational and Mathematical Methods in Medicine [Internet]. http:.www.hindawi.com/journals/ cmmm/2012/219080/.
- Rebrova OJu, 2002. Statistic analysis of medical data. Application software package STATISTICA. Moscow: Mediasfera, 312 p. [Russian].
- Bezrukih MM, Son'kin VD, Farber DA. Physiology of age. Moscow: Publishing Center Academy, 2005, 446 p. [Russian].
- Buchheit M, Gindre C, 2006. Cardiac parasympathetic regulation: respective associations with cardiorespiratory fitness and training load. Am J Physiol Heart Circ Physiol. 291: H451-H458.