Evaluation System Based on EFuNN for On-Line Training Evaluation in Virtual Reality

  • Ronei Marcos de Moraes
  • Liliane dos Santos Machado
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

In this work is proposed a new approach based on Evolving Fuzzy Neural Networks (EFuNNs) to on-line evaluation of training in virtual reality worlds. EFuNNs are dynamic connectionist feed forward networks with five layers of neurons and they are adaptive rule-based systems. Results of the technique application are provided and compared with another evaluation system based on a backpropagation trained multilayer perceptron neural network.

Keywords

Evaluation System Virtual Reality Hide Markov Model Virtual Reality Simulator Virtual Reality System 
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

  1. 1.
    Burdea, G., Coiffet, P.: Virtual Reality Technoloy, 2nd edn. Addison-Wesley, New Jersey (2003)Google Scholar
  2. 2.
    Cohen, J.: A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20, 37–46 (1960)CrossRefGoogle Scholar
  3. 3.
    Kasabov, N.: Evolving Fuzzy Neural Network for Supervised/Unsupervised On-line, Knowledge-based Learning. IEEE Trans. on Man, Machine and Cybernetics 31(6) (2001)Google Scholar
  4. 4.
    Machado, L.S., Moraes, R.M., Zuffo, M.K.: Fuzzy Rule-Based Evaluation for a Haptic and Stereo Simulator for Bone Marrow Harvest for Transplant. In: 5th Phantom Users Group Workshop Proceedings (2000)Google Scholar
  5. 5.
    Machado, L.S., Mello, A.N., Lopes, R.D., Odone Fillho, V., Zuffo, M.K.: A Virtual Reality Simulator for Bone Marrow Harvest for Pediatric Transplant. Studies in Health Technology and Informatics - Medicine Meets Virtual Reality 81, 293–297 (2001)Google Scholar
  6. 6.
    Machado, L.S., Moraes, R.M.: Neural Networks for on-line Training Evaluation in Virtual Reality Simulators. In: Proc. of World Congress on Engineering and Technology Education, Brazil, pp. 157–160 (2004)Google Scholar
  7. 7.
    Mahoney, D.P.: The Power of Touch. Computer Graphics World 20(8), 41–48 (1997)Google Scholar
  8. 8.
    Massie, T., Salisbury, K.: The PHANToM Haptic interface: A device for probing virtual objects. ASME Winter Annual Meeting, DSC 55(1), 295–300 (1994)Google Scholar
  9. 9.
    McBeth, P.B., et al.: Quantitative Methodology of Evaluating Surgeon Performance in Laparoscopic Surgery. Studies in Health Technology and Informatics: Medicine Meets Virt. Real. 85, 280–286 (2002)Google Scholar
  10. 10.
    Moraes, R.M., Machado, L.S.: Fuzzy Hidden Markov Models for on-line Training Evaluation in Virtual Reality Simulators. In: Fuzzy Hidden Markov Models for on-line Training Evaluation in Virtual Reality Simulators. In Computational Intelligent Systems for Applied Research, pp. 296–303. World Scientific, Singapore (2002)Google Scholar
  11. 11.
    Moraes, R.M., Machado, L.S.: Hidden Markov Models for Learning Evaluation in Virtual Reality Simulators. International Journal of Computers & Applications 25(3), 212–215 (2003)Google Scholar
  12. 12.
    Moraes, R.M., Machado, L.S.: Fuzzy Gaussian Mixture Models for on-line Training Evaluation in Virtual Reality Simulators. In: Anals of the International Conference on Fuzzy Information Processing (FIP 2003), Beijing, vol. 2, pp. 733–740 ( March 2003)Google Scholar
  13. 13.
    Rosen, J., Richards, C., Hannaford, B., Sinanan, M.: Hidden Markov Models of Minimally Invasive Surgery. Studies in Health Technology and Informatics - Medicine Meets Virtual Reality 70, 279–285 (2000)Google Scholar
  14. 14.
    Rosen, J., Solazzo, M., Hannaford, B., Sinanan, M.: Objective Laparoscopic Skills Assessments of Surgical Residents Using Hidden Markov Models Based on Haptic Information and Tool/Tissue Interactions. Studies in Health Technology and Informatics - Medicine Meets Virtual Reality 81, 417–423 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ronei Marcos de Moraes
    • 1
  • Liliane dos Santos Machado
    • 2
  1. 1.Department of StatisticsUFPB – Federal University of ParaíbaJoão PessoaBrazil
  2. 2.Department of Computer SciencesUFPB – Federal University of ParaíbaJoão PessoaBrazil

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