An Interoperable and Inclusive User Modeling Concept for Simulation and Adaptation

  • Pradipta Biswas
  • N. Kaklanis
  • Y. Mohamad
  • M. Peissner
  • Patrick Langdon
  • D. Tzovaras
  • Christophe Jung
Part of the Human–Computer Interaction Series book series (HCIS)

Abstract

User models can be considered as explicit representations of the properties of an individual user including user’s needs, preferences as well as physical, cognitive and behavioral characteristics. Due to the wide range of applications, it is often difficult to have a common format or even definition of user models. The lack of a common definition also makes different user models – even if developed for the same purpose -incompatible to each other. It does not only reduce the portability of user models but also restricts new models to leverage benefit from earlier research on similar field. This chapter presents a brief literature survey on user models and concept of an interoperable user model that takes a more inclusive approach than previous research. It is an initiative of the EU VUMS cluster of projects which aims to simulate user interaction and adapt interfaces across a wide variety of digital and non-digital platforms for both able bodied and disabled users. We have already been successful to define an application and platform-independent user model exchange format and the importing of any user profile across all projects.

Keywords

Torque Covariance Glaucoma Paraplegia 

References

  1. 1.
    Anderson, J. R., & Lebiere, C. (1998). The atomic components of thought. Hillsdale: Lawrence Erlbaum Associates.Google Scholar
  2. 2.
    Apkarian, J., Naumann, S., & Cairns, B. (1989). A three-dimensional kinematic and dynamic model of the lower limb. Journal of Biomechanics, 22, 143–155.CrossRefGoogle Scholar
  3. 3.
    Biswas, P., Langdon, P., & Robinson, P. (2012). Designing inclusive interfaces through user modeling and simulation. International Journal of Human Computer Interaction, 28(1). doi: 10.1080/10447318.2011.565718. Taylor & Francis.
  4. 4.
    Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(2–3), 87–129.CrossRefGoogle Scholar
  5. 5.
    Cappelli, T. M., & Duffy, V. G. (2006, July 4–6). Motion capture for job risk classifications incorporating dynamic aspects of work. In Digital human modeling for design and engineering conference, Lyon, SAE International, Warrendale.Google Scholar
  6. 6.
    Carmagnola, F., Cena, F., & Gena, C. (2007). User modeling in the social web. In B. Apolloni, R. J. Howlett, & L. C. Jain (Eds.), Knowledge-based intelligent information and engineering systems (Band 4694 in Lecture notes in computer science, pp. 745–752). Berlin: Springer.CrossRefGoogle Scholar
  7. 7.
    Choi, J. (2008). Developing a 3-dimensional kinematic model of the hand for ergonomic analyses of hand posture, hand space envelope, and tendon excursion. PhD thesis, The University of Michigan.Google Scholar
  8. 8.
    Coluccini, M., Maini, E. S., Martelloni, C., Sgandurra, G., & Cioni, G. (2007). Kinematic characterization of functional reach to grasp in normal and in motor disabled children. Gait Posture, 25(4), 493–501. ISSN 0966-6362. doi: 10.1016/j.gaitpost.2006.12.015
  9. 9.
    DeCarlo, D., Metaxas, D., & Stone, M. (1998). An anthropometric face model using variational techniques. In Proceedings of the 25th annual conference on computer graphics and interactive techniques SIGGRAPH ’98 (pp. 67–74). New York: ACM.Google Scholar
  10. 10.
    DiLorenzo, P. C., Zordan, V. B., & Sanders, B. L. (2008). Laughing out loud: Control for modeling anatomically inspired laughter using audio. ACM Trans Graph, 27(5), 125:1–8.Google Scholar
  11. 11.
    Eng, J. J., & Winter, D. A. (1995). Kinetic analysis of the lower limbs during walking: What information can be gained from a three-dimensional model? Journal of Biomechanics, 28(6), 753–758.CrossRefGoogle Scholar
  12. 12.
    Gajos, K., & Weld, D. S. (2004) SUPPLE: Automatically generating user interfaces. In Proceedings of IUI (pp. 83–100).Google Scholar
  13. 13.
    Garner, B. A., & Pandy, M. G. (2003). Estimation of musculotendon properties in the human upper limb. Annals of Biomedical Engineering, 31, 207–220.CrossRefGoogle Scholar
  14. 14.
    Hingtgen, B. A., McGuire, J. R., Wang, M., & Harris, G. F. (2003, September 17–21). Design and validation of an upper extremity kinematic model for application in stroke rehabilitation, Engineering in Medicine and Biology Society. In Proceedings of the 25th annual international conference of the IEEE (Vol. 2, pp. 1682–1685).Google Scholar
  15. 15.
    Holzbaur, K. R. S., Murray, W. M., & Delp, S. L. (2005). A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control. Annals of Biomedical Engineering, 33, 829–840.CrossRefGoogle Scholar
  16. 16.
    John, B. E., & Kieras, D. (1996). The GOMS family of user interface analysis techniques: Comparison and contrast. ACM Transactions on Computer Human Interaction, 3, 320–351.CrossRefGoogle Scholar
  17. 17.
    Kähler, K., Haber, J., Yamauchi, H., & Seidel, H. P. (2002). Head shop: Generating animated head models with anatomical structure. In ACM SIGGRAPH/EG symposium on computer animation (pp. 55–64).Google Scholar
  18. 18.
    Klyne, G., Reynolds, F., Woodrow, C., Ohto, H., & Butler, M. H. (Eds.). (2002). Composite capability/preference profiles (CC/PP): Structure and vocabularies. W3C Working Draft 08 November 2002. World Wide Web Consortium. Available at: http://www.w3.org/TR/CCPP-struct-vocab/. Accessed 12 Dec 2012.
  19. 19.
    Kobsa, A., Koenemann, J., & Pohl, W. (2001). Personalised hypermedia presentation techniques for improving online customer relationships. The Knowledge Engineering Review, 16(2), S. 111–S. 155. Cambridge University Press.Google Scholar
  20. 20.
    Komura, T., Shinagawa, Y., & Kunii, T. L. (2000). Creating and retargeting motion by the musculoskeletal human body model. The Visual Computer, 16(5), 254–270.CrossRefGoogle Scholar
  21. 21.
    Koo, T. K., Mak, A. F., & Hung, L. K. (2002). In vivo determination of subject-specific musculotendon parameters: Applications to the prime elbow flexors in normal and hemiparetic subjects. Clinical Biomechanics, 17(5), 390–399, ISSN 0268-0033. doi: 10.1016/S0268-0033(02)00031-1
  22. 22.
    Laitila, L. (2005). Datormanikinprogram om verktyg vid arbetsplatsutformning – En kritisk studie av programanvändning. Thesis, Luleå Technical University, Luleå.Google Scholar
  23. 23.
    Lamkull, D., Hanson, L., & Ortengren, R. (2009). A comparative study of digital human modeling simulation results and their outcomes in reality: A case study within manual assembly of automobiles. International Journal of Industrial Ergonomics, 39, 428–441.CrossRefGoogle Scholar
  24. 24.
    Lassila, O., & Swick, R. R. (Eds.). (1999). Resource description framework (RDF), model and syntax specification. W3C recommendation 22 February 1999. World Wide Web Consortium. Available at: http://www.w3.org/TR/REC-rdf-syntax/. Accessed 12 Dec 2012.
  25. 25.
    Lee, S. H., & Terzopoulos, D. (2006). Heads up! Biomechanical modeling and neuromuscular control of the neck. ACM Trans Graph, 25(3), 1188–1198. Proceedings of ACM SIGGRAPH 06.Google Scholar
  26. 26.
    Ouerfelli, M., Kumar, V., & Harwin, W. S. (1999). Kinematic modeling of head-neck movements. IEEE Transactions Systems, Man and Cybernetics, Part A: Systems and Humans, 29(6), 604–615. doi: 10.1109/3468.798064, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=798064&isnumber=17313
  27. 27.
    Pai, Y. C., & Patton, J. L. (1997). Center of mass velocity-position predictions for balance control. Journal of Biomechanics, 11, 341–349.Google Scholar
  28. 28.
    Pai, Y. C., & Patton, J. L. (1998). Erratum: Center of mass velocity-position predictions for balance control. Journal of Biomechanics, 31, 199.CrossRefGoogle Scholar
  29. 29.
    Pai, Y. C., Rogers, M. W., Patton, J. L., Cain, T. D., & Hanke, T. (1998). Static versus dynamic predictions of protective stepping following waist-pull perturbations in young and older adults. Journal of Biomechanics, 31, 1111–1118.CrossRefGoogle Scholar
  30. 30.
    Paternò, F. (1999). Model based design and evaluation of interactive applications. Berlin: Springer.Google Scholar
  31. 31.
    Patton, J. L., Lee, W. A., & Pai, Y. C. (2000). Relative stability improves with experience in a dynamic standing task. Experimental Brain Research, 135, 117–126.CrossRefGoogle Scholar
  32. 32.
    Patton, J. L., Pai, Y. C., & Lee, W. A. (1997). A simple model of the feasible limits to postural stability. Presented at IEEE/Engineering in Medicine an Biology Society meeting, Chicago.Google Scholar
  33. 33.
    Pennestrì, E., Stefanelli, R., Valentini, P. P., & Vita, L. (2007). Virtual musculo-skeletal model for the biomechanical analysis of the upper limb. Journal of Biomechanics, 40(6), 1350–1361, ISSN 0021-9290. doi: 10.1016/j.jbiomech.2006.05.013. http://www.sciencedirect.com/science/article/pii/S0021929006001679
  34. 34.
    Porter, J., Case, K., Freer, M. T., & Bonney, M. C. (1993). Automotive ergonomics, Chapter. In computer-aided ergonomics design of automobiles. London: Taylor & FrancisGoogle Scholar
  35. 35.
    Prince, F., Corriveau, H., Hebert, R., & Winter, D. A. (1997). Gait in the elderly. Gait Posture, 5(2), 128–135(8).Google Scholar
  36. 36.
    Rao, S. S., Bontrager, E. L., Gronley, J. K., Newsam, C. J., & Perry, J. (1996). Three dimensional kinematics of wheelchair propulsion. IEEE Transactions on Rehabilitation Engineering, 4, 152–160.CrossRefGoogle Scholar
  37. 37.
    Sapin, E., Goujon, H., de Almeida, F., Fodé, P., & Lavaste, F. (2008). Functional gait analysis of trans-femoral amputees using two different single-axis prosthetic knees with hydraulic swing-phase control: Kinematic and kinetic comparison of two prosthetic knees. Prosthetics and Orthotics International, 32(2), 201–218.CrossRefGoogle Scholar
  38. 38.
    Shapiro, A., Faloutsos, P., & Ng-Thow-Hing, V. (2005). Dynamic animation and control environment. In Proceedings of graphics interface (pp. 61–70).Google Scholar
  39. 39.
    Van Nierop, O. A., Van der Helm, A., Overbeeke, K. J., & Djajadiningrat, T. J. (2008). A natural human hand model. The Visual Computer, 24(1), 31–44.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Pradipta Biswas
    • 1
  • N. Kaklanis
    • 2
  • Y. Mohamad
    • 3
  • M. Peissner
    • 4
  • Patrick Langdon
    • 1
  • D. Tzovaras
    • 2
  • Christophe Jung
    • 5
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK
  2. 2.Information Technologies InstituteCentre for Research and Technology HellasThessalonikiGreece
  3. 3.Fraunhofer FITSankt AugustinGermany
  4. 4.Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO, Leiter Competence Center Human-Computer InteractionStuttgartGermany
  5. 5.Fraunhofer IGDDarmstadtGermany

Personalised recommendations