Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles
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 autocorrelati...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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2013
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| _version_ | 1826297817958711296 |
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| author | Khovanova, N Khovanov, I Sbano, L Griffiths, F Holt, T |
| author_facet | Khovanova, N Khovanov, I Sbano, L Griffiths, F Holt, T |
| author_sort | Khovanova, N |
| collection | OXFORD |
| description | 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. © 2012 Elsevier Ireland Ltd. |
| first_indexed | 2024-03-07T04:37:25Z |
| format | Journal article |
| id | oxford-uuid:d0710790-6c9b-40a3-80c7-dd5b2eac7965 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:37:25Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:d0710790-6c9b-40a3-80c7-dd5b2eac79652022-03-27T07:49:51ZCharacterisation of linear predictability and non-stationarity of subcutaneous glucose profilesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d0710790-6c9b-40a3-80c7-dd5b2eac7965EnglishSymplectic Elements at Oxford2013Khovanova, NKhovanov, ISbano, LGriffiths, FHolt, TContinuous 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. © 2012 Elsevier Ireland Ltd. |
| spellingShingle | Khovanova, N Khovanov, I Sbano, L Griffiths, F Holt, T Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title | Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title_full | Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title_fullStr | Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title_full_unstemmed | Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title_short | Characterisation of linear predictability and non-stationarity of subcutaneous glucose profiles |
| title_sort | characterisation of linear predictability and non stationarity of subcutaneous glucose profiles |
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