Our aim with Beauty Technology is to transform our body in an interactive platform by hiding technology into beauty products for creating muscle based interfaces that don’t give the wearer a cyborg look. FX e-makeup is a Beauty Technology prototype that applies FX makeup materials embedded with electronics for sensing the face’s muscles. This work presents Winkymote and Kinisi as proof of concept of the FX e-makeup.


Wearable Computers Beauty Technology Electronic Makeup Muscle Based Interface 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Vega, K.F.C., Fuks, H.: Empowering electronic divas through beauty technology. In: Marcus, A. (ed.) DUXU/HCII 2013, Part III. LNCS, vol. 8014, pp. 237–245. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    Vega, K.: Exploring the power of feedback loops in wearables computers. In: Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction, TEI 2013, pp. 371–372. ACM, New York (2013)Google Scholar
  3. 3.
    Vega, K., Fuks, H.: Beauty technology as an interactive computing platform. In: Proceedings of the 2013 ACM International Conference on Interactive Tabletops and Surfaces, ITS 2013, pp. 357–360. ACM, New York (2013)CrossRefGoogle Scholar
  4. 4.
    Jain, A.K., Li, S.Z.: Handbook of Face Recognition. Springer-Verlag New York, Inc., Secaucus (2005)Google Scholar
  5. 5.
    Lin, M., Li, B.: A wireless EOG-based human computer interface. Biomedical Engineering and Informatics (BMEI) 5, 1794–1796 (2010)Google Scholar
  6. 6.
    Curran, E., Sykacek, P., Stokes, M., Roberts, S., Penny, W., Johnsrude, I., Owen, A.: Cognitive tasks for driving a brain-computer interfacing system: a pilot study. IEEE Transactions on Neural Systems and Rehabilitation Engineering 12(1), 48–54 (2004)CrossRefGoogle Scholar
  7. 7.
    Tanaka, K., Matsunaga, K., Kanamori, N., Hori, S., Wang, H.: Electroencephalogram-based control of a mobile robot. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, vol. 2, pp. 688–693 (2003)Google Scholar
  8. 8.
    Fabiani, G., McFarland, D., Wolpaw, J., Pfurtscheller, G.: Conversion of eeg activity into cursor movement by a brain-computer interface (bci). IEEE Transactions on Neural Systems and Rehabilitation Engineering 12(3), 331–338 (2004)CrossRefGoogle Scholar
  9. 9.
    Kanade, T., Cohn, J., Tian, Y.: Comprehensive database for facial expression analysis. In: Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 46–53 (2000)Google Scholar
  10. 10.
    Izard, C.E.: The maximally discriminative facial movement coding system. University of Delaware (1979)Google Scholar
  11. 11.
    Ekman, P., Friesen, W.: Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto (1978)Google Scholar
  12. 12.
    Scherer, K., Ekman, P.: Handbook of methods in nonverbal behavior research, pp. 45–135. Cambridge University Press, New York (1982)Google Scholar
  13. 13.
    Chambayil, B., Singla, R., Jha, R.: Virtual keyboard BCI using eye blinks in EEG. In: 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 466–470 (2010)Google Scholar
  14. 14.
    Królak, A., Strumiłło, P.: Eye-blink detection system for human-computer interaction. Universal Access in the Information Society 11(4), 409–419 (2012)CrossRefGoogle Scholar
  15. 15.
    Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J.: Measuring facial expressions by computer image analysis. Psychophysiology 36, 253–263 (1999)CrossRefGoogle Scholar
  16. 16.
    Cohn, J.F., Zlochower, A.J., Lien, J., Kanade, T.: Automated face analysis by feature point tracking has high concurrent validity with manual facs coding. Psychophysiology 36, 35–43 (1999)CrossRefGoogle Scholar
  17. 17.
    Pantic, M., Patras, I., Rothkruntz, L.: Facial action recognition in face profile image sequences. In: IEEE International Conference on Multimedia and Expo, vol. 1, pp. 37–40 (2002)Google Scholar
  18. 18.
    Singla, R., Chambayil, B., Khosla, A., Santosh, J.: Comparison of SVM and ANN for classification of eye events in EEG. Journal of Biomedical Science and Engineering 4, 62–69 (2011)CrossRefGoogle Scholar
  19. 19.
    Rantanen, V., Venesvirta, H., Spakov, O., Verho, J., Vetek, A., Surakka, V., Lekkala, J.: Capacitive measurement of facial activity intensity. IEEE Sensors Journal 13(11), 4329–4338 (2013)CrossRefGoogle Scholar
  20. 20.
    Manabe, D.: Daito manabe, (accessed April 4, 2010)
  21. 21.
    Saponas, T.S., Kelly, D., Parviz, B.A., Tan, D.S.: Optically sensing tongue gestures for computer input. In: Proceedings of the 22nd Annual ACM Symposium on User Interface Software and Technology, UIST 2009, pp. 177–180. ACM, New York (2009)Google Scholar
  22. 22.
    Vega, K.: Conductive makeup, (accessed April 4, 2010)
  23. 23.
    Gallagher, S.: Self-reference and schizophrenia: A cognitive model of immunity to error through misidentification. In: Exploring the Self: Philosophical and Psychopathological Perspectives on Self-Experience, pp. 203–239. John Benjamins (2000)CrossRefGoogle Scholar
  24. 24.
    Tsakiris, M., Prabhu, G., Haggard, P.: Having a body versus moving your body: How agency structures body-ownership. Consciousness and Cognition 15(2), 423–432 (2006)CrossRefGoogle Scholar
  25. 25.
    Tsakiris, M., Schutz-Bosbach, S., Gallagher, S.: On agency and body-ownership: Phenomenological and neurocognitive reflections. Consciousness and Cognition 16(3), 645–660 (2007)CrossRefGoogle Scholar
  26. 26.
    William, E.R.: The neuropsychology of facial expression: A review of the neurological and psychological mechanisms for producing facial expressions. Psychological Bulletin 95, 52–77 (1984)CrossRefGoogle Scholar
  27. 27.
    Duchenne de Boulogne, G.B.: The Mechanism of Human Facial Expression. Cambridge University Press (1990)Google Scholar
  28. 28.
    Paul Ekman, G.R., Hager, J.C.: Deliberate facial movement. Child Development 51, 886–891 (1980)CrossRefGoogle Scholar
  29. 29.
    Gosselin, P., Perron, M., Beaupr, M.: The voluntary control of facial action units in adults. Emotion 10, 266–271 (2010)CrossRefGoogle Scholar
  30. 30.
    Vega, K.: Kinisi, (accessed January 20, 2014)
  31. 31.
    Lathem, P.A., Gregorio, T.L., Garber, S.L.: High-level quadriplegia: an occupational therapy challenge. The American Journal of Occupational Therapy 39, 705–714 (2008)CrossRefGoogle Scholar
  32. 32.
    Sipski, M.L., Richards, J.S.: Spinal cord injury rehabilitation, state of the science. American Journal of Physical Medicine & Rehabilitation 95, 310–342 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Katia Vega
    • 1
  • Abel Arrieta
    • 2
  • Felipe Esteves
    • 3
  • Hugo Fuks
    • 1
  1. 1.Department of InformaticsPUC-RioRio de JaneiroBrazil
  2. 2.Department of Mechanical EngineeringPUC-RioRio de JaneiroBrazil
  3. 3.Department of AdministrationPUC-RioRio de JaneiroBrazil

Personalised recommendations