Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles.

Journal article

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.

Authors: Khovanova, N; Khovanov, I; Sbano, L; Griffiths, F; Holt, T

• Publication status: Published
• Journal: Computer methods and programs in biomedicine
• Volume: 110
• Issue: 3
• Pages: 260-267
• Publication date: 2013-06-01
• DOI: 10.1016/j.cmpb.2012.11.009
• EISSN: 1872-7565
• ISSN: 0169-2607
• Language: English
• Keywords: Models, Biological; Linear Models; Monitoring, Physiologic; Case-Control Studies; Middle Aged; Diabetes Mellitus, Type 1; Humans; Glucose; Stochastic Processes; Young Adult; Female; Adult; Subcutaneous Tissue; Diabetes Mellitus, Type 2; Aged; Male; Blood Glucose