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AffectAura: an intelligent system for emotional memory

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Published:05 May 2012Publication History

ABSTRACT

We present AffectAura, an emotional prosthetic that allows users to reflect on their emotional states over long periods of time. We designed a multimodal sensor set-up for continuous logging of audio, visual, physiological and contextual data, a classification scheme for predicting user affective state and an interface for user reflection. The system continuously predicts a user's valence, arousal and engage-ment, and correlates this with information on events, communications and data interactions. We evaluate the interface through a user study consisting of six users and over 240 hours of data, and demonstrate the utility of such a reflection tool. We show that users could reason forward and backward in time about their emotional experiences using the interface, and found this useful.

References

  1. Aigner, W., Miksch, S., Schumann, H. and Tominski,C. Visualization of Time-Oriented Data. Springer, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Boehner, K., DePaula, R., Dourish, P. and Sengers, P. Affect: from information to interaction. In Proc. CC'05, ACM (2005), 59--68. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Boucsein, W. Electrodermal Activity. Springer-Verlag, New York, 1992.Google ScholarGoogle Scholar
  4. Bradley, M.M. and Lang, P.J. Measuring emotion: the self-assessment manikin and the semantic differential. J Behav Ther Exp Psy, 25, 1 (1994), 49--59.Google ScholarGoogle ScholarCross RefCross Ref
  5. Brush, AJ, Meyers, B.R., Tan, D.S. and Czerwinski, M. Understanding memory triggers for task tracking. In Proc. CHI'07, ACM (2007), 947--950. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cahill, L. and McGaugh, J.L. A novel demonstration of enhanced memory associated with emotional arousal. Conscious Cogn, 4 (1995), 410--421.Google ScholarGoogle ScholarCross RefCross Ref
  7. Cootes, T.F., Edwards, G.J. and Taylor, C.J. Active appearance models. IEEE Pattern Anal (2001), 681--685. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J. et al. Active shape models-their training and application. Comput Viz Image Und (1995), 38--59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Daily, S. B. and Picard, R. W. Girls Involved in Real Life Sharing: Utilizing Technology to Support the Emotional Development of Teenaged Girls, J School Counseling, 5,1(2007), 20.Google ScholarGoogle Scholar
  10. De la Torre, F. and Agell, C. Multimodal Diaries. In Proc. ICME '07 (2007), IEEE, 839--842.Google ScholarGoogle Scholar
  11. Dietz, R. and Lang, A. Affective agents: Effects of agent affect on arousal, attention, liking and learning. In Proc. COGNITIVE'11, (1999).Google ScholarGoogle Scholar
  12. Donath, J., Dragulescu, A., Zinman, A., and Viegas, F. Data portraits. In Art Gallery ACM SIGGRAPH (2010). Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ebbinghaus, H. (1885). Memory: A Contribution to Experimental Psychology. Tran.Ruger & Bussenius(1913).Google ScholarGoogle Scholar
  14. El Kaliouby, R., Teeters, A. and Picard, R.W. Invited Talk: An Exploratory Social-Emotional Prosthetic for Autism Spectrum Disorders. In BSN'06, (2006), IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Fernandez, R. A computational model for the automatic recognition of affect in speech. Massachusetts Institute of Technology, 2004.Google ScholarGoogle Scholar
  16. Goldberger, J. and Roweis, S. and Hinton, G. and Salakhutdinov, R. Neighbourhood Components Analysis. In Proc. NIPS'04, MIT (2004).Google ScholarGoogle Scholar
  17. Healy, J. and Picard, R. W. StartleCam: A cybernetic Wearable Camera, In Proc. 2nd International Symposium on Wearable Computers, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Higgins, E.T. Beyond pleasure and pain. Am Psychol (1997), 1280.Google ScholarGoogle Scholar
  19. Fogarty, J., Ko, A.J., Aung, H.H., Golden, E., Tang, K.P. and Hudson, S.E. Examining task engagement in sensor-based statistical models of human interruptibility. Proc. CHI', ACM (2005), 331--340. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Jax, P. and Vary, P. On artificial bandwidth extension of telephone speech. Signal Processing (2003), 1707--1719. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Kapoor, A. and Picard, R.W. Multimodal affect recognition in learning environments. In Proc. MULTIMEDIA'05 ( 2005), ACM, 677--682. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Larsen, R.J. and Diener, E. Promises and problems with the circumplex model of emotion. Pers Soc Psychol Rev (1992), 25--59.Google ScholarGoogle Scholar
  23. Liu, K.K.L. A personal, mobile system for understanding stress and interruptions. MIT, 2004.Google ScholarGoogle Scholar
  24. Loewenstein, G. and Lerner, J.S. The role of affect in decision making. In Handbook of affective science. Oxford University Press, Oxford, 2003.Google ScholarGoogle Scholar
  25. Nicolaou, M.A., Gunes, H. and Pantic, M. Continuous Prediction of Spontaneous Affect from Multiple Cues and Modalities in Valence-Arousal Space. IEEE T Affect Comput (2011). Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Poh, M.Z., Swenson, N.C. and Picard, R.W. A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. IEEE T Bio-med Eng (2010).Google ScholarGoogle Scholar
  27. Shotton, J., Fitzgibbon, A., et al. Real-time human pose recognition in parts from single depth images. In Proc. CVPR'11, IEEE (2011), 1297--1304. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Singer, E. The Measured Life. Technology Review (July/August 2011).Google ScholarGoogle Scholar
  29. Ståhl, A., Höök, K., Svensson, M., Taylora, A. and Combetto, M. Experiencing the affective diary. Pers Ubiquit Comput (2009), 365--378. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Suls, J., Green, P. and Hillis, S. Emotional reactivity to everyday problems, affective inertia, and neuroticism. Pers Soc Psychol B (1998), 127.Google ScholarGoogle Scholar
  31. Viégas, F., Golder, S. and Donath J. Visualizing email content: portraying relationships from conversational histories. In Proc. CHI'06, ACM (2006), 979--988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Walker, W.R. and Skowronski, J.J. and Thompson, C.P. Life is pleasant-and memory helps to keep it that way! Rev Gen Psychol (2003), 203.Google ScholarGoogle Scholar

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        cover image ACM Conferences
        CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
        May 2012
        3276 pages
        ISBN:9781450310154
        DOI:10.1145/2207676

        Copyright © 2012 ACM

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        Publication History

        • Published: 5 May 2012

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