Advertisement

Ambient Intelligence and Simulation in Health Care Virtual Scenarios

  • António Abelha
  • Cesar Analide
  • José Machado
  • José Neves
  • Manuel Santos
  • Paulo Novais
Part of the IFIP — The International Federation for Information Processing book series (IFIPAICT, volume 243)

Abstract

The success of change depends greatly on the ability to respond to human needs and to bridge the gap between humans and machines, and understanding the environment. With such experience, in addition to extensive practice in managing change, knowledge sharing and innovation, it would be interesting in offering a contribution by facilitating a dialogue, knowledge café (i.e. bringing in knowledge) on these issues, and how to apply them to new and altering scenarios. When one comes into the area of health care, one major limitation felt by those institutions is in the selection process of physicians to undertake a specific task, where there is a lack of objective, of validated measures of human performance. Indeed, objective measures are necessary if simulators are to be used to evaluate the skills and training of medical practitioners and teams or to evaluate the impact of new processes or equipment design on the overall system performance. In this paper it will be presented a logical theory of Situation Awareness (SA) and discusses the methods required for developing an objective measure of SA within the context of a simulated medical environment, as the one referred to above. Analysis and interpretation of SA data for both individual and team performance in health care are presented.

Keywords

Electronic Medical Record Logic Program Situation Awareness Collaborative Network Medical Information 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.
    Picard, R. What does it mean for a computer to have emotions?; In Trappl, R.; Petta, P., and Payr, S. (eds) Emotions in Human and Artefacts, 2003.Google Scholar
  2. 2.
    Weiss, G. (ed), Multi-Agent Systems: A Modern Approach to Distributed Artificial Intelligence, Cambridge, M.A., MIT Press, 1999.Google Scholar
  3. 3.
    Machado J., Abelha A., Santos M. and Neves J., Multi-agent Based Problem Solving in Medical Decision Support Systems, in Proc. of the 2nd International Conference on Knowledge Engineering and Decision Support, Lisbon, 2006.Google Scholar
  4. 4.
    Abelha, A., PhD Thesis, “Multi-agent systems as Working Cooperative Entities in Health Care Units” (In Portuguese), Universidade do Minho, Braga, Portugal, 2004.Google Scholar
  5. 5.
    Abelha A., Machado J., Alves V. e Neves J., Data Warehousing through Multi-Agent Systems in the Medical Arena, in Proceedings of the 1 st International Conference on Knowledge Engineering and Decision Support, Porto, Portugal, 2004.Google Scholar
  6. 6.
    Machado J., Abelha A., Neves J. and Santos M., Ambient Intelligence in Medicine, in proc. of the IEEE Biomedical Circuits and Systems Conference, Healthcare Technology, Imperial College, London, UK, 2006.Google Scholar
  7. 7.
    Abelha A., Santos M., Machado J. and Neves J., Auditing Agents in the Context of a Telemedical Information Society, in Knowledge and Decision Technologies, Vale Z., Ramos C. and Faria L. (eds), Lisbon, Portugal (ISBN: 972-8688-39-3), 2006.Google Scholar
  8. 8.
    Machado J. and Alves V., Web-based Simulation in Medicine, in Proceedings of the European Simulation and Modelling Conference, MODELLING AND SIMULATION 2005, Feliz Teixeira JM, Brito AEC (eds), Porto, 2005.Google Scholar
  9. 9.
    Grudin, J., Group Dynamics and Ubiquitous computing, Comm. of the ACM, 45, 12, 2002.CrossRefGoogle Scholar
  10. 10.
    Analide, C., Novais, P., Machado, J., and Neves, J. Quality of Knowledge in Virtual Entities, in Encyclopedia of Communities of Practice in Information and Knowledge Management, Idea Group Inc., 436–442, 2006.Google Scholar
  11. 11.
    Kaltenborn K. and Rienhoff O., “Virtual reality in medicine”, Meth. Inform. Med., 32(5), 407–417, 1993.Google Scholar
  12. 12.
    Björklind, A., Holmlid, S., “Ambient intelligence to go”, White paper on mobile intelligent ambience, 2003.Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2007

Authors and Affiliations

  • António Abelha
    • 1
  • Cesar Analide
    • 1
  • José Machado
    • 1
  • José Neves
    • 1
  • Manuel Santos
    • 2
  • Paulo Novais
    • 1
  1. 1.Departamento de InformáticaUniversidade do MinhoBragaPortugal
  2. 2.Departamento de Sistemas de InformaçãoUniversidade do MinhoGuimarãesPortugal

Personalised recommendations