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 language | English (US) |
|---|---|
| Pages (from-to) | 16-27 |
| Number of pages | 12 |
| Journal | Algorithms |
| Volume | 4 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 2011 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Clustering algorithm
- Diabetes
- Glucose management
- Laplacian eigenmap
- Piecewise linear approximation
- Wavelet
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