University of Canterbury Home
    • Admin
    UC Research Repository
    UC Library
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    1. UC Home
    2. Library
    3. UC Research Repository
    4. Faculty of Engineering | Te Kaupeka Pūhanga
    5. Engineering: Conference Contributions
    6. View Item
    1. UC Home
    2.  > 
    3. Library
    4.  > 
    5. UC Research Repository
    6.  > 
    7. Faculty of Engineering | Te Kaupeka Pūhanga
    8.  > 
    9. Engineering: Conference Contributions
    10.  > 
    11. View Item

    Using a stochastic model to detect unusual continuous glucose monitor behaviour in newborn infants (2012)

    Thumbnail
    View/Open
    12640777_Signal - CGM Stochastic classification v1.2 - submitted.pdf (333.2Kb)
    Type of Content
    Conference Contributions - Published
    UC Permalink
    http://hdl.handle.net/10092/7364
    
    Publisher's DOI/URI
    https://doi.org/10.3182/20120829-3-HU-2029.00032
    
    Publisher
    University of Canterbury. Mechanical Engineering
    Collections
    • Engineering: Conference Contributions [2307]
    Authors
    Signal, M.
    Le Compte, A.J.
    Harris, D.L.
    Weston, P.J.
    Harding, J.E.
    Chase, Geoff cc
    show all
    Abstract

    Abnormal blood glucose (BG) concentrations have been associated with negative outcomes in critically ill adults and infants. Diagnosis of hyperglycaemia and hypoglycaemia is by BG measurements, which are typically taken several hours apart due to the clinical effort required. Continuous glucose monitoring (CGM) devices, which take measurements every 5 minutes, have the potential to improve the detection and diagnosis of these glycaemic abnormalities. There have been relatively few successful investigations of CGM devices in the ICU, and one study reported significant sensor noise. If CGM devices are going to be used in the clinical setting to monitor, diagnose and potentially help treat glycaemic abnormalities, clinicians need to know data are reliable and accurate. This study uses CGM data from neonatal infants to develop a tool that will aid clinicians in identifying unusual CGM behaviour. A stochastic model was created to classify CGM measurements with the aim of highlighting unusual CGM behaviour. In addition, the method uses a colour coded CGM trace to convey the information quickly and efficiently, either retrospectively or in real-time. The method has been used to detect unusual hypoglycaemic events and potential sensor degradation, both of which need to be interpreted with care. Overall, while BG measurements are required to make definitive conclusions about glycaemic events, the stochastic model provides another level of information to aid users in interpretation and decision making.

    Citation
    Signal, M., Le Compte, A.J., Harris, D.L., Weston, P.J., Harding, J.E., Chase, J.G. (2012) Using a stochastic model to detect unusual continuous glucose monitor behaviour in newborn infants. Budapest, Hungary: 8th IFAC Symposium on Biological and Medical Systems (BMS12), 29-31 Aug 2012. Biological and Medical Systems, 8, 1, 248-253.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    hypoglycaemia; continuous glucose monitoring; modelling; detection; critically ill; infant; preterm
    ANZSRC Fields of Research
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinology
    40 - Engineering::4003 - Biomedical engineering::400305 - Biomedical instrumentation
    Rights
    https://hdl.handle.net/10092/17651

    Related items

    Showing items related by title, author, creator and subject.

    • Impact of calibration algorithms on hypoglycaemia detection in newborn infants using continuous glucose monitors 

      Signal, M.; Le Compte, A.J.; Harris, D.L.; Weston, P.J.; Harding, J.E.; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2012)
      Neonatal hypoglycaemia is a common condition that can cause seizures and serious brain injury in infants. It is diagnosed by blood glucose (BG) measurements, often taken several hours apart. Continuous glucose monitoring ...
    • Continuous glucose monitoring in newborn infants: Effect of calibration measurements and detected hypoglycaemia 

      Thomas, F.; Signal, M.K.; Harris, D.L.; Weston, P.J.; Harding, J.E.; Shaw, Geoff; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2013)
      Neonatal glycaemia is highly variable and can cause serious brain injury if uncontrolled [1]. However, monitoring infants’ blood glucose (BG) levels via frequent BG measurements is not achievable due to a lack of blood and ...
    • Detecting unusual continuous glucose monitor measurements: A stochastic model approach 

      Signal, M.K.; Harris, D.L.; Weston, P.J.; Le Compte, A.J.; Chase, Geoff; Harding, J.E. for the CHYLD Study Group (University of Canterbury. Mechanical Engineering, 2012)
    Advanced Search

    Browse

    All of the RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThesis DisciplineThis CollectionBy Issue DateAuthorsTitlesSubjectsThesis Discipline

    Statistics

    View Usage Statistics
    • SUBMISSIONS
    • Research Outputs
    • UC Theses
    • CONTACTS
    • Send Feedback
    • +64 3 369 3853
    • ucresearchrepository@canterbury.ac.nz
    • ABOUT
    • UC Research Repository Guide
    • Copyright and Disclaimer
    • SUBMISSIONS
    • Research Outputs
    • UC Theses
    • CONTACTS
    • Send Feedback
    • +64 3 369 3853
    • ucresearchrepository@canterbury.ac.nz
    • ABOUT
    • UC Research Repository Guide
    • Copyright and Disclaimer