Chaikovsky I. A.1, Kalnysh V. V.2, Krivova O. A.3, Kozak L. M.3, Vyrovoy Y. S.1, Frolov Y. A.1


1Glushkov Institute of Cybernetics, Kyiv

2SI "Institute for occupational health of NAMS of Ukraine", Kyiv 3IRTC IT a S of NAS of Ukraine, Kyiv

Full article (PDF), RUS

Introduction. Heart rate variability (HRV) research is of great importance not only for assessment of the functional state of the body, but also for diagnostics of emotional reactions. The lack of a unique relation between changes of HRV indices and emotional reactions remains to be a great problem. Furthermore, in the practice of HRV analysis there is no consensus in respect of the list of HR indices, recommended for classifying and identification of emotional reactions.

Purpose of the study. To identify a set of informative HRV indices to be used as an objective criterion for assessment of emotional reactions in operators (on emotionally significant video clips).

Materials and methods. In order to analyze a subjective component of emotional reactions in operators (29 persons) on three test video (positive, negative, and neutral from the FilmStim database) there have been used psychophysiological methods. The objective component was studied using ECG-monitoring with 48 indices of HRV, obtained by hourly, spectral, geometric and nonlinear methods of analysis. Statistical analyses were performed using a statistical software package STATISTICA 10. The multivariate analysis of variance (MANOVA) was used to analyze the effect of video clips.

Results. The data were explored to meet the assumptions for using MANOVA. One-way MANOVA revealed that 6 indicators of emotional reactions (2 self-report measures and 4 HRV measures HR, SI, LF, MF) were statistically significant (Wilks' Lambda = 0,525, F = 4,306, p < 0,001) with effect size of eta2 = 0,22. We analyzed these 6 informative indicators, using different post-hoc univariate F test for between-stimuli comparison. Also, Mann-Whitney U test and Kruskal-Walls H-test were used for variables (SI, LF) with non-Gaussian distribution. Stepwise linear discriminant analysis was performed to identify a new informative feature set, consisting of the most significant indicators for improving the classification of emotional reactions. The total average classification accuracy of 4 states in operators achieved 95,68 %.

Conclusions. In the present study it has been developed a method of statistical analysis of subjective and objective components of operators’ reaction on different emotional modality stimuli. The method covers: descriptive, multivariate analysis of variance, linear discriminant analysis. It was shown that indices of HRV (HR, average R-R intervals, SI, LF, MF) and some others (PNN50, ND, SampEn, LXS) can be reasonably considered as physiological markers for measurement of emotional reactions.

Key words: heart rate variability, emotionally significant situations, emotional reaction, MANOVA, linear discriminant analysis


  1. Payne, E. F. 2003, "Definition of emotions", Journal of BEM, V. 4, no. 3, pp. 38–43.
  2. Bayevskiy, R. M., Ivanov, G. G. Chireikin, L. V. 2001, "Analysis of heart rate variability in the use of different electric cardiac systems", Vestnik aritmologii, no. 24, pp. 65–87 (in Russian).
  3. McCraty, R., Atkinson, M., Tiller, W. [et al.] 1995, "The effects of emotions on short term heart rate variability using power spectrum analysis", American Journal of Cardiology, no. 6, pp. 1089–1093.
  4. Lyonfields, J. D., Borkovec, T. D., Thayer, J. F. 1995, "Vagal tone in generalized anxiety disorder and the effects of aversive imagery and worrisome thinking", Behavior Therapy, v. 26, no. 3, pp. 457–466.
  5. Hjortskov, N., Rissen, D., Blangsted, A. K. [et al.] 2004, "The effect of mental stress on heart rate variability and blood pressure during computer work", Eur. J. Appl. Physiol., v. 92, no. 1–2, pp. 84–89.
  6. McCraty, R. 2006, "Emotional stress, positive emotions, and psychophysiological coherence", Stress in Health and Disease. Wiley-VCH, Weinheim, pp. 2–30.
  7. Rainville, P., Bechara, A,. Naqv, N., Damasio, A. 2006, "Basic emotions are associated with distinct patterns of cardiorespiratory activity", International Journal of Psychophysiology, v. 61, no. 1, pp. 5–18.
  8. Мashin, V. А., Мashina, M. N. 2004, "Classification of the functional states and diagnostics of psychoemotional stability on the basis of the factorial indices of the heat rate variability", Ross. fiziol. J. im. I. M. Sechenova, v. 90, no. 12, pp. 1508–1521 (in Russian].
  9. Kolodyazhniy, V., Kreibig, S., Roth, W. [et. al.] 2011, "An affective computing approach to physiological emotion specificity: Towards subject-independent and stimulus-independent classification of film-induced emotions", Psychophysiology, v. 48, pp. 908–922.
  10. Kreibig, S. D. 2010, "Autonomic nervous system activity in emotion: A review", Biological Psychology, v. 84, pp. 394–421.
  11. Taelman, J., Vandeput, S., Spaepen, A, Van Huffel S. 2009, "Influence of mental stress on heart rate and heart rate variability”, 4th European Conference of the International Federation for Medical and Biological Engineering", IFMBE Proceedings, v. 22, pp. 1366–1369.
  12. Stroud, L, Salovey, P, Epel, E., 2002, "Sex differences in stress responses: social rejection versus achievement stress", Biol. Psychol., v. 52, pp. 318–327.
  13. Appelhans, B. M., Luecken, L. J. 2006, "Heart rate variability an index of regulated emotional responding", Rev. Gen. Psychol., no. 10, pp. 229–240.
  14. Thayer, J., Ihs F., Fredrikson, M. [et. al.], 2012, "A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health", Neuroscience Biobehav. Rev., v. 36, pp. 747–756.
  15. FilmStim database
  16. Ilyin, E. P. 2005, Psychophysiology of human states, SPb: Piter, pp. 412 (in Russian).
  17. Chaikovskyi, I. A., Kalnysh, V. V., Ena T. A., et. al. 2011, "Possibilities of analysis of heart rate variability in diagnostics of human emotional state", Medychna informatika i inzheneriya, no. 1, pp. 57–62 (in Ukrainan).
  18. Kalnysh, V. V., Ena T. A., Chaikovskyi, I. A., Krivo- va O. A. et. al. 2013, "Multivariate statistical analysis of objective and subjective component in reaction to emotional exposure: methodical aspects", Klinicheskaya informatika i meditsina, no. 10, pp. 175–76 (in Russian).
  19. Cohen, J. 1988, Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, N J : Erlbaum, pp. 596.
  20. Мashin, V. А., 2007, "Psychic load, psychic strain and functional state of operators of control systems", Voprosy psikhologii, no. 6, pp. 86–96 (in Russian).
  21. International standard ISO 10075:1991 Ergonomic principles related to mental work-load : General terms and definitions catalogue_detail.htm.csnumber=18045
  22. Kramer, A. F. 1991, Physiological metrics of mental workload: A review of recent progress. Damos D. L. (Ed.) Multiple-Task performance. London : Taylor and Francis, pp. 279–328.
  23. Myrtek, M., Brugner, G., Muller, W. 1996, Validation studies of emotional, mental and physical workload components in the field. Fahrenberg J., Myrtek M. (Eds.) Ambulatory assessment. Computer-assisted psychological and psychophysiological methods in monitoring and field studies. Seattle, WA: Hogrefe & Huber, pp. 287–304.
  24. Richards, J. E., Casey, B. J. 1991, "Heart rate variability during attention phases in young infants", Psychophysiology, v. 28, no. 1, pp. 43–53.
  25. Gross, J., Levenson, R. 1997, "Hiding Feelings: The acute effects of inhibiting negative and positive emotion", Journal of Abnormal Psychology, v. 106, no. 1, pp. 95–103.
  26. Chaikovskyi, I. 2006, "Intraindividual variability of T-wave shape on electrocardiogram as indicator of stress", Proc. of 33-rd International Congress on Electrocardiology. Koln, Germany, pp. 28.
  27. Oxley, D. R., Smith, K. B., Alford, J. R., Hibbing, M. V. et. al. 2008, "Political attitudes vary with physiological traits", Science, v. 321, pp. 1667–1670.