Abstract
To improve human-computer interaction (HCI), computers need to recognize and respond properly to their user’s emotional state. This is a fundamental application of affective computing, which relates to, arises from, or deliberately influences emotion. As a first step to a system that recognizes emotions of individual users, this research focuses on how emotional experiences are expressed in six parameters (i.e., mean, absolute deviation, standard deviation, variance, skewness, and kurtosis) of not baseline-corrected physiological measurements of the galvanic skin response (GSR) and of three electromyography signals: frontalis (EMG1), corrugator supercilii (EMG2), and zygomaticus major (EMG3). The 24 participants were asked to watch film scenes of 120 seconds, which they rated afterward. These ratings enabled us to distinguish four categories of emotions: negative, positive, mixed, and neutral. The skewness and kurtosis of the GSR, the skewness of the EMG2, and four parameters of EMG3, discriminate between the four emotion categories. This, despite the coarse time windows that were used. Moreover, rapid processing of the signals proved to be possible. This enables tailored HCI facilitated by an emotional awareness of systems.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Ball, G. and Breese, J.: Modeling the emotional state of computer users. In: Workshop on Attitude, Personality and Emotions in User-Adapted Interaction, Banff, Canada (1999).
Bosma, W. and Andre, E.: Exploiting emotions to disambiguate dialogue acts. In: Proceedings of the 9th International Conference on Intelligent User Interface, Funchal, Madeira, Portugal, ACM Press: New York, NY, USA (2004) 85–92.
Boucsein, W.: Electrodermal Activity, Plenum Press, NY, 1992.
Cacioppo, J.T. and Dorfman, D.D.: Waveform movement analysis in psychophysiological research. Psychological Bulletin 102 (1987) 421–438.
Cacioppo, J.T., Marshall-Goodell, B. and Dorfman, D.D.: Skeletal muscular patterning: Topographical analysis of the integrated electromyogram. Psychophysiology 20 (1983) 269–283.
Ceaparu, I., Lazar, J., Bessiere, K., Robinson, J. and Shneiderman, B.: Determining causes and severity of end-user frustration. International Journal of Human-Computer Interaction 17 (2004) 333–356.
Gross, J.J. and Levenson, R.W.: Emotion elicitation using films. Cognition and Emotion 9 (1995) 87–108.
Hess, U., Kappas, A., McHugo, G.J., Kleck, R.E. and Lanzetta, J.T.: Analysis of the encoding and decoding of spontaneous and posed smiles: The use of facial electromyography. Journal of Nonverbal Behavior 13 (1989) 121–137.
Hilty, D.M., Marks, S.L., Urness, D., Yellowlees, P.M. and Nesbitt, T.S.: Clinical and educational telepsychiatry applications: A review. The Canadian Journal of Psychiatry 49 (2004) 12–23.
Hone, K., Akhtar, F. and Saffu, M.: Affective agents to reduce user frustration: the role of agent embodiment. In: Proceedings of Human-Computer Interaction (HCI2003), Bath, UK (2003).
Konijn, E.A. and Hoorn, J.F.: Some like it bad. Testing a model for perceiving and experiencing fictional characters. Media Psychology 7 (2005) 107–144.
Lang, P.J.: The emotion probe: Studies of motivation and attention. American Psychologist 52 (1995) 372–385.
Lang, P.J., Bradley, M.M. and Cuthbert, B.N.: Emotion, motivation, and anxiety: Brain mechanisms and psychophysiology. Biological Psychiatry 44 (1998) 1248–1263.
Larsen, J.T., Norris, C.J. and Cacioppo, J.T.: Effects of positive and negative affect on electromyographic activity over zygomaticus major and corrugator supercilii. Psychophysiology 40 (2003) 776–785.
Matzler, K., Faullant, R., Renzl, B. and Leiter, V.: The relationship between personality traits (extraversion and neuroticism), emotions and customer self-satisfaction. Innovative Marketing 1 (2005) 32–39.
Merriam-Webster, Incorporated: Merriam-Webster Online. URL: http://www.m-w.com/. [Last accessed on February 27, 2007].
Ortony, A., Clore, G.L. and Collins, A.: The Cognitive Structure of Emotions. Cambridge, New York: Cambridge University Press (1988).
Oviatt, S.L., Darves, C. and Coulston, R.: Toward adaptive conversational interfaces: Modeling speech convergence with animated personas. ACM Transactions on Computer-Human Interaction 11 (2004) 300–328.
Picard, R.: Affective computing for HCI. In: Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces. Volume 1, Lawrence Erlbaum Associates, Inc: Mahwah, NJ, USA (1999) 829–833.
Picard, R.: Affective Computing. Boston MA.: MIT Press (1997).
Picard, R.W.: Toward computers that recognize and respond to user emotion. IBM Systems Journal 39 (2000) 705–719.
Picard., R.W. and Scheirer, J.: The galvactivator: A glove that senses and communicates skin conductivity. In: Proceedings of the 9th International Conference on Human-Computer Interaction, New Orleans (2001).
Press, W.H., Flannery, B.P., Teukolsky, S.A. and Vetterling, W.T.: Numerical recipes in C: The art of scientific computing. 2nd edition. Cambridge, England: Cambridge University Press (1992).
Scerbo, M.W., Freeman, F.G., Mikulka, P.J., Parasuraman, R. and Di Nocero, F.: The efficacy of psychophysiological measures for implementing adaptive technology. Technical Report NASA/TP-2001–211018, NASA Center for AeroSpace Information (CASI) (2001).
Van den Broek, E.L.: Emotional Prosody Measurement (EPM): A voice-based evaluation method for psychological therapy effectiveness. Studies in Health Technology and Informatics (Medical and Care Compunetics 1) 103 (2004) 118–125.
Van den Broek, E.L., Schut, M.H., Westerink, J.H.D.M., Van Herk, J., and Tuinenbreijer, K., Computing Emotion Awareness Through Facial Electromyography, in: Thomas S. Huang, Nicu Sebe, Michael S. Lew, Vladimir Pavlovic, Mathias Kölsch, Aphrodite Galata, Branislav Kisacanin (Eds), Lecture Notes in Computer Science, Volume 3979/2006, ISBN: 3–540–34202–8, Computer Vision in Human-Computer Interaction: ECCV 2006 Workshop on HCI, Graz, Austria, May 13, 2006. Proceedings, pages 52–63
Weisstein, E.W.: CRC Concise Encyclopedia of Mathematics. 2nd edition. Chapman & Hall/CRC: USA (2002).
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer
About this chapter
Cite this chapter
Westerink, J.H.D.M., van den Broek, E., Schut, M., van Herk, J., Tuinenbreijer, K. (2008). Computing Emotion Awareness Through Galvanic Skin Response and Facial Electromyography. In: Westerink, J.H.D.M., Ouwerkerk, M., Overbeek, T.J.M., Pasveer, W.F., de Ruyter, B. (eds) Probing Experience. Philips Research, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6593-4_14
Download citation
DOI: https://doi.org/10.1007/978-1-4020-6593-4_14
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-6592-7
Online ISBN: 978-1-4020-6593-4
eBook Packages: Computer ScienceComputer Science (R0)