Knowledge-based decision support for patient monitoring in cardioanesthesia

  • Thomas Schecke
  • Manfred Langen
  • Hans-Joachim Popp
  • Günter Rau
  • Horst Käsmacher
  • Günter Kalff
Article

DOI: 10.1007/BF01145897

Cite this article as:
Schecke, T., Langen, M., Popp, HJ. et al. J Clin Monit Comput (1992) 9: 1. doi:10.1007/BF01145897

Abstract

An approach to generating ‘intelligent alarms’ is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between ‘normal’ and ‘below normal’, are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia.

Key words

anesthesia artificial intelligence Computer-Assisted Decision Making Computer-Assisted Therapy Physiologic Monitoring 

Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • Thomas Schecke
    • 1
  • Manfred Langen
    • 1
  • Hans-Joachim Popp
    • 1
  • Günter Rau
    • 1
  • Horst Käsmacher
    • 2
  • Günter Kalff
    • 2
  1. 1.Helmholtz-Institute for Biomedical EngineeringAachen University of TechnologyAachenGermany
  2. 2.Clinic of Anesthesiology, Medical FacultyAachen University of TechnologyAachenGermany

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