Predictability of unplanned extubations


Acute life threatening events such as cardiac/respiratory arrests are often predictable in adults and children. However critical events such as unplanned extubations are considered as not predictable. This paper seeks to evaluate the ability of automated prediction systems based on feature space embedding and time series methods to predict unplanned extubations in paediatric intensive care patients. We try to exploit the trends in the physiological signals such as Heart Rate, Respiratory Rate, Systolic Blood Pressure and Oxygen saturation levels in the blood using signal processing aspects of a frame-based approach of expanding signals using a nonorthogonal basis derived from the data. We investigate the significance of the trends in a computerised prediction system. The results are compared with clinical observations of predictability. We will conclude by investigating whether the prediction capability of the system could be exploited to prevent future unplanned extubations.

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Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Mathematics
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
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Event Title: 2014 IEEE-EMBS international conference on Biomedical and Health Informatics
Event Type: Other
Event Dates: 2014-06-01 - 2014-06-04
Uncontrolled Keywords: Biomedical Engineering,Health Informatics
ISBN: 978-1-4799-2131-7
Full Text Link: http://ieeexplo ... rnumber=6864409
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2014
Authors: Matam, B.R.
Fule, B.K.
Duncan, H.P.
Lowe, D.



Version: Accepted Version

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