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Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles
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Khovanova, N. A., Khovanov, I. A., Sbano, L., Griffiths, Frances and Holt, Tim A. (2013) Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles. Computer Methods and Programs in Biomedicine, Volume 110 (Number 3). pp. 260-267. doi:10.1016/j.cmpb.2012.11.009 ISSN 0169-2607.
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WRAP_Khovanova_0873262-es-110113-characterization_of_linear_predictability_and_non-stationarity_of_subcutaneous_glucose_profiles.pdf - Accepted Version Download (741Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.cmpb.2012.11.009
Abstract
Continuous glucose monitoring is increasingly used in the management of diabetes. Subcutaneous glucose profiles are characterised by a strong non-stationarity, which limits the application of correlation-spectral analysis. We derived an index of linear predictability by calculating the autocorrelation function of time series increments and applied detrended fluctuation analysis to assess the non-stationarity of the profiles. Time series from volunteers with both type 1 and type 2 diabetes and from control subjects were analysed. The results suggest that in control subjects, blood glucose variation is relatively uncorrelated, and this variation could be modelled as a random walk with no retention of ‘memory’ of previous values. In diabetes, variation is both greater and smoother, with retention of inter-dependence between neighbouring values. Essential components for adequate longer term prediction were identified via a decomposition of time series into a slow trend and responses to external stimuli. Implications for diabetes management are discussed.
| Item Type: | Journal Article | ||||
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| Subjects: | Q Science > QP Physiology R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Science, Engineering and Medicine > Research Centres > Centre for Complexity Science Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Social Science & Systems in Health (SSSH) |
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| Library of Congress Subject Headings (LCSH): | Diabetes -- Mathematical models, Non-insulin-dependent diabetes -- Mathematical models, Blood sugar -- Mathematical models, Blood sugar monitoring | ||||
| Journal or Publication Title: | Computer Methods and Programs in Biomedicine | ||||
| Publisher: | Elsevier Ireland Ltd. | ||||
| ISSN: | 0169-2607 | ||||
| Official Date: | June 2013 | ||||
| Dates: |
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| Volume: | Volume 110 | ||||
| Number: | Number 3 | ||||
| Page Range: | pp. 260-267 | ||||
| DOI: | 10.1016/j.cmpb.2012.11.009 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Date of first compliant deposit: | 23 December 2015 | ||||
| Date of first compliant Open Access: | 23 December 2015 | ||||
| Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||
| Grant number: | EP/C53932X/2 (EPSRC) |
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