• DocumentCode
    3064255
  • Title

    The use of mathematical models and clinical knowledge in intraoperative vital sign trend monitoring

  • Author

    Yang, Ping

  • Author_Institution
    Department of Electrical and Computer Engineering, the University of British Columbia, Vancouver, CANADA
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    1028
  • Lastpage
    1028
  • Abstract
    Trend monitoring is a fundamental step in intelligent patient monitoring. When a patient experiences a systemic physiological change, the first sign is very often that a relevant vital-sign trend signal has changed direction. Notifying the decision makers about trend changes help them track vital sign dynamics leading to early diagnosis should an adverse event occur. Furthermore, due to homoeostatic compensation, a patient´s physiological status can be clinically stable with vital signs at different levels following intraoperative treatments. To understand patient´s status, the numerical levels of vital signs should be analyzed together with the trend characteristics, including the temporal patterns (direction, duration, and trend speed) and the interrelationship between the changes in different variables.
  • Keywords
    Biomedical monitoring; Hidden Markov models; Mathematical model; Patient monitoring; Pollution measurement; Predictive models; Signal analysis; Signal processing; Statistical analysis; Testing; Computer Simulation; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Expert Systems; Intraoperative Care; Models, Biological; Monitoring, Physiologic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4649332
  • Filename
    4649332