Emotion in Motion: A Study of Music and Affective Response

  • Javier Jaimovich
  • Niall Coghlan
  • R. Benjamin Knapp
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7900)

Abstract

‘Emotion in Motion’ is an experiment designed to understand the emotional responses of people to a variety of musical excerpts, via self-report questionnaires and the recording of electrodermal activity (EDA) and heart rate (HR) signals. The experiment ran for 3 months as part of a public exhibition in Dublin, having nearly 4000 participants and over 12000 listening samples. This paper presents the methodology used by the authors to approach this research, as well as preliminary results derived from the self-report data and the physiology.

Keywords

Emotion Music Autonomic Nervous System ANS Physiological Database Electrodermal Activity EDR EDA POX Heart Rate HR Self-Report Questionnaire 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    The Geneva Emotional Music Scales (GEMS) | zentnerlab.com, http://www.zentnerlab.com/psychological-tests/geneva-emotional-music-scales (retrieved January 20, 2013)
  2. 2.
    Tomkins, S.S.: Affect Imagery Consciousness - Volume II The Negative Affects. Springer Publishing Company (1963)Google Scholar
  3. 3.
    Ekman, P., Friesen, W.V.: The repertoire of nonverbal behavior: Categories, origins, usage, and coding. Semiotica I, 49–98 (1969)Google Scholar
  4. 4.
    Salimpoor, V.N., Benovoy, M., Larcher, K., Dagher, A., Zatorre, R.J.: Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nature Neuroscience 14, 257–262 (2011)CrossRefGoogle Scholar
  5. 5.
    Zentner, M., Grandjean, D., Scherer, K.R.: Emotions evoked by the sound of music: Characterization, classification, and measurement. Emotion 8, 494–521 (2008)CrossRefGoogle Scholar
  6. 6.
    Juslin, P.N., Västfjäll, D.: Emotional responses to music: the need to consider underlying mechanisms. Behav Brain Sci. 31, 559–575; discussion 575–621 (2008)Google Scholar
  7. 7.
    Balteş, F.R., Avram, J., Miclea, M., Miu, A.C.: Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting: A scientist’s tribute to Maria Callas. Brain and Cognition 76, 146–157 (2011)CrossRefGoogle Scholar
  8. 8.
    Trost, W., Ethofer, T., Zentner, M., Vuilleumier, P.: Mapping Aesthetic Musical Emotions in the Brain. Cerebral Cortex (2011)Google Scholar
  9. 9.
    Gabrielsson, A., Juslin, P.N.: Emotional Expression in Music Performance: Between the Performer’s Intention and the Listener’s Experience. Psychology of Music 24, 68–91 (1996)CrossRefGoogle Scholar
  10. 10.
    Ekman, P.: An argument for basic emotions. Cognition & Emotion 6, 169–200 (1992)CrossRefGoogle Scholar
  11. 11.
    Russell, J.A.: A circumplex model of affect. Journal of Personality and Social Psychology 39, 1161–1178 (1980)CrossRefGoogle Scholar
  12. 12.
    Villon, O., Lisetti, C.: Toward Recognizing Individual’s Subjective Emotion from Physio-logical Signals in Practical Application. In: Twentieth IEEE International Symposium on Computer-Based Medical Systems, 2007, pp. 357–362. IEEE (2007)Google Scholar
  13. 13.
    Wilhelm, F.H., Grossman, P.: Emotions beyond the laboratory: Theoretical fundaments, study design, and analytic strategies for advanced ambulatory assessment. Biological Psychology 84, 552–569 (2010)CrossRefGoogle Scholar
  14. 14.
    Lantelme, P., Milon, H., Gharib, C., Gayet, C., Fortrat, J.O.: White Coat Effect and Reactivity to Stress: Cardiovascular and Autonomic Nervous System Responses. Hypertension 31, 1021–1029 (1998)CrossRefGoogle Scholar
  15. 15.
    Bradley, M.M., Lang, P.J.: Emotion and Motivation. In: Handbook of Psychophysiology, pp. 581–607 (2007)Google Scholar
  16. 16.
    Cacioppo, J.T., Bernston, G.G., Larsen, J.T., Poehlmann, K.M., Ito, T.A.: The Psychophy-siology of Emotion, pp. 173–191. Guilford Press (2000)Google Scholar
  17. 17.
    Kreibig, S.D., Wilhelm, F.H., Roth, W.T., Gross, J.J.: Cardiovascular, electrodermal, and respiratory response patterns to fear- and sadness-inducing films. Psychophysiology 44, 787–806 (2007)CrossRefGoogle Scholar
  18. 18.
    Picard, R.W.: Affective Computing, M.I.T Media Laboratory, Cambridge, MA (1997)Google Scholar
  19. 19.
    Kim, J., André, E.: Emotion Recognition Based on Physiological Changes in Music Lis-tening. IEEE Transactions on Pattern Analysis and Machine Intelligence 30, 2067–2083 (2008)CrossRefGoogle Scholar
  20. 20.
    Huisman, G., Van Hout, M.: Using induction and multimodal assessment to understand the role of emotion in musical performance. In: Emotion in HCI – Designing for People, Liverpool, pp. 5–7 (2008)Google Scholar
  21. 21.
    Bradley, M.M., Lang, P.J.: Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry 25, 49–59 (1994)CrossRefGoogle Scholar
  22. 22.
    Likert, R.: A technique for the measurement of attitudes. Archives of Psychology; Archives of Psychology 22(140), 55 (1932)Google Scholar
  23. 23.
    Boucsein, W.: Electrodermal Activity. Springer, New York (2012)CrossRefGoogle Scholar
  24. 24.
    Juslin, P.N., Sloboda, J.A.: Music and Emotion: Theory and Research. Oxford University Press (2001)Google Scholar
  25. 25.
    Lykken, D.T., Venables, P.H.: Direct Measurement of Skin Conductance: A Proposal for Standardization. Psychophysiology 8, 656–672 (1971)CrossRefGoogle Scholar
  26. 26.
    Healey, J., Picard, R.W.: Digital processing of affective signals. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 6, pp. 3749–3752. Media Lab., MIT, Cambridge (1998)Google Scholar
  27. 27.
    Bechara, A., Damasio, H., Damasio, A.R., Lee, G.P.: Different Contributions of the Human Amygdala and Ventromedial Prefrontal Cortex to Decision-Making. J. Neurosci. 19, 5473–5481 (1999)Google Scholar
  28. 28.
    Haag, A., Goronzy, S., Schaich, P., Williams, J.: Emotion Recognition Using Bio-Sensors: First Steps Towards an Automatic System. In: André, E., Dybkjær, L., Minker, W., Heisterkamp, P. (eds.) ADS 2004. LNCS (LNAI), vol. 3068, pp. 36–48. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  29. 29.
    Wilder, J.: The “law of initial values,” a neglected biological law and its significance for research and practice. Zeitschrift für die gesammte Neurologie und Psychiatrie 137, 317–324 (1931)CrossRefGoogle Scholar
  30. 30.
    Lacey, J.I.: The Evaluation of Autonomic Responses: Toward a General Solution. Annals of the New York Academy of Sciences 67, 125–163 (1956)CrossRefGoogle Scholar
  31. 31.
    Agelink, M., Malessa, R., Baumann, B., Majewski, T., Akila, F., Zeit, T., Ziegler, D.: Standardized tests of heart rate variability: normal ranges obtained from 309 healthy humans, and effects of age, gender, and heart rate. Clinical Autonomic Research 11, 99–108 (2001)CrossRefGoogle Scholar
  32. 32.
    Rajendra Acharya, U., Paul Joseph, K., Kannathal, N., Lim, C., Suri, J.: Heart rate varia-bility: a review. Medical and Biological Engineering and Computing 44, 1031–1051 (2006)CrossRefGoogle Scholar
  33. 33.
    Liao, D., Barnes, R.W., Chambless, L.E., Simpson Jr., R.J., Sorlie, P., Heiss, G.: The ARIC Investigators: Age, race, and sex differences in autonomic cardiac function measured by spectral analysis of heart rate variability—The ARIC study. The American Journal of Cardiology 76, 906–912 (1995)CrossRefGoogle Scholar
  34. 34.
    Jensen-Urstad, K., Storck, N., Bouvier, F., Ericson, M., Lindblad, L.E., Jensen-Urstad, M.: Heart rate variability in healthy subjects is related to age and gender. Acta Physiol. Scand. 160, 235–241 (1997)CrossRefGoogle Scholar
  35. 35.
    Ostchega, Y., Porter, K.S., Hughes, J., Dillon, C.F., Nwankwo, T.: Resting Pulse Rate Reference Data for Children, Adolescents, and Adults: United States, 1999–2008. National Health Statistics Report 41, 1–16 (2011)Google Scholar
  36. 36.
    Kannel, W.B., Kannel, C., Paffenbarger Jr., R.S., Cupples, L.A.: Heart rate and cardiovas-cular mortality: The Framingham study. American Heart Journal 113, 1489–1494 (1987)CrossRefGoogle Scholar
  37. 37.
    Kostis, J.B., Moreyra, A.E., Amendo, M.T., Di Pietro, J., Cosgrove, N., Kuo, P.T.: The effect of age on heart rate in subjects free of heart disease. Studies by Ambulatory Electro-Cardiography and Maximal Exercise Stress Test. Circulation 65, 141–145 (1982)Google Scholar
  38. 38.
    Tsuji, H., Venditti, F.J., Manders, E.S., Evans, J.C., Larson, M.G., Feldman, C.L., Levy, D.: Reduced heart rate variability and mortality risk in an elderly cohort. The Framingham Heart Study. Circulation. 90, 878–883 (1994)CrossRefGoogle Scholar
  39. 39.
    Kuch, B., Hense, H.W., Sinnreich, R., Kark, J.D., Von Eckardstein, A., Sapoznikov, D., Bolte, H.D.: Determinants of short-period heart rate variability in the general population. Cardiology 95, 131–138 (2001)CrossRefGoogle Scholar
  40. 40.
    Sloboda, J.A.: Music Structure and Emotional Response: Some Empirical Findings. Psychology of Music 19, 110–120 (1991)CrossRefGoogle Scholar
  41. 41.
    Panksepp, J.: The Emotional Sources of “Chills” Induced by Music. Music Perception 13, 171–207 (1995)CrossRefGoogle Scholar
  42. 42.
    Grewe, O., Nagel, F., Kopiez, R., Altenmüller, E.: How Does Music Arouse “Chills”? Investigating Strong Emotions, Combining Psychological, Physiological, and Psychoac-oustical Methods. Annals of the New York Academy of Sciences 1060, 446–449 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Javier Jaimovich
    • 1
  • Niall Coghlan
    • 1
  • R. Benjamin Knapp
    • 2
  1. 1.Sonic Arts Research CentreQueen’s University BelfastUK
  2. 2.Institute for Creativity, Arts, and TechnologyVirginia TechUSA

Personalised recommendations