Name
Title | ||
|---|---|---|
Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.cmpb.2012.11.009 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
autocorrelation,diabetes mellitus,detrended fluctuation analysis | Diabetes mellitus,Predictability,Random walk,Computer science,Type 2 diabetes,Diabetes management,Decomposition of time series,Detrended fluctuation analysis,Statistics,Autocorrelation | Journal |
Volume | Issue | ISSN |
110 | 3 | 0169-2607 |
Citations | PageRank | References |
4 | 0.64 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| N. A. Khovanova | 1 | 23 | 2.72 |
| I. A. Khovanov | 2 | 5 | 3.11 |
| L. Sbano | 3 | 8 | 1.18 |
| F. Griffiths | 4 | 4 | 0.64 |
| T. A. Holt | 5 | 4 | 0.64 |