Advertisement

Neuroscience and Behavioral Physiology

, Volume 46, Issue 4, pp 375–381 | Cite as

EEG Correlates of the Functional State of Pilots during Simulated Flights

  • V. N. Kiroi
  • E. V. Aslanyan
  • O. M. Bakhtin
  • N. R. Minyaeva
  • D. M. Lazurenko
Article
  • 41 Downloads

Analysis of variance and discriminant analysis were used to study EEG spectral characteristics recorded using 15 leads from two professional pilots with more than 15 years of experience, in the frequency band 0.1–70 Hz, during flights on a TU-154 simulator, including takeoff, landing (including in difficult conditions), and horizontal flight. The results showed that the spectral characteristics of the EEG were highly informative measures of the ongoing functional state of the pilots at different phases of flight. The high significance of the differences seen in the individual features showed them to be nonrandom and demonstrated the potential for using EEG parameters to construct a system for monitoring the pilot’s state at all stages of flight.

Keywords

EEG functional state spectral characteristics air flights 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aslanyan, E. V. and Kiroy, V. N., “Electroencephalographic evidence on the strategies of adaptation to the factors of monotony,” Span. J. Psychol., 12, No. 1, 32–45 (2009).CrossRefPubMedGoogle Scholar
  2. Aslanyan, E. V., Effects of Individual-Typological Characteristics on the Dynamics of Functional Status in Humans in Conditions of Monotonous Activity: Auth. Abstr. Mast. Thesis in Biol. Sci., Res. Inst. Neu rocybernetics, Rostov State Univ., Rostov-on-Don (2002).Google Scholar
  3. Bekhtereva, N. P. and Nagornaya, Zh. V., “Dynamics of EEG coherence on performance of tasks involving nonverbal (imaginary) creativity,” Fiziol. Cheloveka, 33, No. 5, 5–13 (2007).PubMedGoogle Scholar
  4. Boeing. Statistical Summary of Commercial Jet Airplane Accidents Worldwide Operations 1959–2010, Boeing, June 2011.Google Scholar
  5. Boitsova, Yu. A. and Dan’ko, S. G., “Changes in the EEG on comparison of the resting state with the eyes open and closed in the dark,” Fiziol. Cheloveka, 36, No. 3, 138–141 (2010).PubMedGoogle Scholar
  6. Borghini, G., Astolfi, L., Vecchiato, G., et al., “Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness,” Neurosci. Biobehav. Rev. (2012).Google Scholar
  7. Bushov, Yu. V., Svetlik, M. V., and Krutenkova, E. P., “Gamma activity in the cerebral cortex: link with intellect and the accuracy of time reproduction,” Fiziol. Cheloveka, 36, No. 4, 15–21 (2010).PubMedGoogle Scholar
  8. CAANL. Civil Aviation Safety Data, 1993–2007, Civil Aviation Authority of the Transport and Water Management Inspectorate Netherlands (CAANL) (2008).Google Scholar
  9. Dumenko, V. N., “Functional signifi cance of the high-frequency components of brain electrical activity during the processes of the formation of the internal organs,” Zh. Vyssh. Nerv. Deyat., 52, No. 5, 539–550 (2002).Google Scholar
  10. Gordeev, S. A., “Characteristics of brain bioelectrical activity at high levels of anxiety in humans,” Fiziol. Cheloveka, 33, No. 4, 11–17 (2007).PubMedGoogle Scholar
  11. Hart, S. C. and Staveland, L. E., Development of NASA-TLX (Task Load Index) Results of Empirical and Theoretical Research, Yancock, P. A. and Meshkati, N. (eds.), Human Mental Workload, North Holland Press, Amsterdam (2011).Google Scholar
  12. Holm, A., Lukander, K., Korpela, J., et al., “Estimating brain load from the EEG,” Sci. World J., No. 9, 639–651 (2009).Google Scholar
  13. Ioffe, M. E., Mechanisms of Motor Learning, Nauka, Moscow (1991). Kiroi, V. N. and Aslanyan, E. V., “General features of the formation of the state of monotony,” Zh. Vyssh. Nerv. Deyat., 55, No. 6, 768–776 (2005).Google Scholar
  14. Kiroi, V. N. and Chorayan, O. G., “Theories of neuron ensembles in the brain,” Usp. Fiziol. Nauk., 31, No. 2, 23–39 (2000).PubMedGoogle Scholar
  15. Lindsley, D. B., “The reticular system in the process of separate perception,” in: The Reticular Formation of the Brain [Russian translation], Medgiz, Moscow (1962), pp. 451–470.Google Scholar
  16. Lopes da Silva F. H., “Neural mechanisms underlying brain waves: from neural membranes to networks,” EEG and Clin. Neurophysiol., 79, No. 2, 81–93 (1991).Google Scholar
  17. Palva, S. and Palva, J. M., “New vistas for alpha-frequency band oscillations,” Trends. Neurosci., 30, No. 4, 150–158 (2007).CrossRefPubMedGoogle Scholar
  18. Safety Management Manual (SMM), International Civil Aviation Authority (ICAO) Press (2006).Google Scholar
  19. Shul’gina, G. I., “Genesis of the rhythms of biopotentials and its role in information processing,” Fiziol. Cheloveka, 31, No. 3, 59–71 (2005).PubMedGoogle Scholar
  20. Sviderskaya, N. E. and Antonov, A. G., “Effects of individual psychological characteristics on going to spatial organization of the EEG in nonverbal/divergent thought,” Fiziol. Cheloveka, 34, No. 5, 34–43 (2008).Google Scholar
  21. Ushakov, I. B. and Bednenko, V. S., “An on-board medical support system for pilots of potential space stations,” Fiziol. Cheloveka, 36, No. 3, 5–11 (2010).PubMedGoogle Scholar
  22. Varshavskaya, L. V., Human Brain Bioelectrical Activity during Continuous, Long-Term, and Tense Mental Activity: Auth. Abstr. Mast. Thesis in Biol. Sci., Res. Inst. Neurocybernetics, Rostov State Univ.,Google Scholar
  23. Rostov-on-Don (1996). Vidulich, M. A. and Wickens, C. D., “Causes of dissociation between subjective workload measures and performance,” Appl. Ergonom., 17, 291–296 (1986).Google Scholar
  24. Williamson, A. M., Feyer, A., and Friswell, R., “The impact of work practices on fatigue in long distance truck drivers,” Accid. Anal. Prevent., 28, No. 6, 709–719 (1996).CrossRefGoogle Scholar
  25. Yeh, Y. Y. and Wickens, C. D., “Dissociation of performance and subjective measures of workload,” Human Fact., 30, 111–120 (1988).Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • V. N. Kiroi
    • 1
  • E. V. Aslanyan
    • 1
  • O. M. Bakhtin
    • 1
  • N. R. Minyaeva
    • 1
  • D. M. Lazurenko
    • 1
  1. 1.Academy of Biology and Biotechnology and Research Institute of NeurocyberneticsSouthern Federal UniversityRostov-on-DonRussia

Personalised recommendations