Virtual Sport System for Optimum Exercising Based on a User Model

  • Kazumoto Tanaka
  • Takayuki Kataoka
  • Makoto Hasegawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5670)


It is said that improving movement habits is effective to solve the problem of obesity. In this paper, we describe a physically interactive computer game system that can control a game mode to let a user maintain an appropriate exercise load based on an estimation of the user’s heart rate state. We propose a Bayesian network model that can estimate heart rate states. The model calculates probability distribution of a heart rate state using user’s motion features. We also describe an experimental validation of the system.


Physically interactive computer game Exercise load Heart rate state estimation User model Bayesian network 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mokka, S., Väätänen, A., Heinilä, J., et al.: Fitness Computer Game with A Bodily User Interface. In: 2nd International Conference on Entertainment Computing, pp. 1–3 (2003)Google Scholar
  2. 2.
    Höysniemi, J., Aula, A., Auvinen, P., et al.: Shadow Boxer - A Physically Interactive Fitness Game. In: 3rd Nordic Conference on Human-computer Interaction, pp. 389–392 (2004)Google Scholar
  3. 3.
    Soh, M., Junichi, H.: An Exercise Game Reflecting Heart Rate. The Journal of The Society for Art and Science 6(3), 136–144 (2007)CrossRefGoogle Scholar
  4. 4.
    Nenonen, V., Lindblad, A., Häkkinen, V., et al.: Using Heart Rate to Control An Interactive Game. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 853–856 (2007)Google Scholar
  5. 5.
    Bayesian network from Wikipedia,
  6. 6.
    Kai-min, C., Joseph, B., Jack, M., Albert, C.: A Bayes Net Toolkit for Student Modeling in Intelligent Tutoring Systems. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 104–113. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Van Dan, N., Kameyama, M.: Bayesian-Networks-Based Motion Estimation for a Highly-Safe Intelligent Vehicle. In: SICE-ICASE International Joint Conference, pp. 6023–6026 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kazumoto Tanaka
    • 1
  • Takayuki Kataoka
    • 1
  • Makoto Hasegawa
    • 1
  1. 1.Department of Information and Systems Engineering, School of EngineeringKinki UniversityHiroshimaJapan

Personalised recommendations