Quantification of the variability of continuous glucose monitoring data

Edward Aboufadel, Robert Castellano, Derek Olson

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Several measurements are used to describe the behavior of a diabetic patient's blood glucose. We describe a new, wavelet-based algorithm that indicates a new measurement called a PLA index could be used to quantify the variability or predictability of blood glucose. This wavelet-based approach emphasizes the shape of a blood glucose graph. Using continuous glucose monitors (CGMs), this measurement could become a new tool to classify patients based on their blood glucose behavior and may become a new method in the management of diabetes.

Original languageEnglish (US)
Pages (from-to)16-27
Number of pages12
JournalAlgorithms
Volume4
Issue number1
DOIs
StatePublished - Mar 1 2011

Keywords

  • Clustering algorithm
  • Diabetes
  • Glucose management
  • Laplacian eigenmap
  • Piecewise linear approximation
  • Wavelet

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