Carlos Cervigón
ABSTRACT
People with diabetes need to have their glucose levels under control, and it is essential for them to be able to know or estimate their glucose levels at any time. Continuous glucose monitors are commonly used, which measure interstitial glucose, an approximation of blood glucose, by means of a small catheter. Although most devices are not very intrusive, they do present some discomfort, and it would be preferable if these glucose levels could be estimated non-invasively, for example, through other physiological measurements collected in a simple way. This abstract describes our research on the performance of different grammatical evolution techniques to obtain accurate estimations of actual subcutaneous glucose values from non-invasive physiological measures, steps, calories and heart rates obtained with commercial smartwatches.
- J. Ignacio Hidalgo, J. Manuel Colmenar, Gabriel Kronberger, Stephan M. Winkler, Oscar Garnica, and Juan Lanchares. 2017. Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods. Journal of Medical Systems 41, 9 (08 Aug 2017), 142. Google Scholar
Digital Library
- David C. Klonoff. 2008. Personalized Medicine for Diabetes. Journal of Diabetes Science and Technology 2, 3 (2008), 335--341. PMID: 19885196. Google ScholarCross Ref
Index Terms
- Estimation of Interstitial Glucose from physical activity measures using Grammatical Evolution
Recommendations
Predicting Glycemia in Diabetic Patients By Evolutionary Computation and Continuous Glucose Monitoring
GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference CompanionDiabetes mellitus is a disease that affects more than three hundreds million people worldwide. Maintaining a good control of the disease is critical to avoid not only severe long-term complications but also dangerous short-term situations. Diabetics ...
A genetic programming-based regression for extrapolating a blood glucose-dynamics model from interstitial glucose measurements and their first derivatives
AbstractThis paper illustrates the development and the applicability of an Evolutionary Computation approach to enhance the treatment of Type-1 diabetic patients that necessitate insulin injections. In fact, being such a disease associated to ...
Graphical abstractDisplay Omitted
Highlights- A regression method for estimating blood glucose from interstitial one is presented.
Reducing high-risk glucose forecasting errors by evolving interpretable models for Type 1 diabetes
AbstractDiabetes mellitus is a metabolic disease involving high blood glucose levels that can lead to serious medical consequences. Hence, for diabetic patients the prediction of future glucose levels is essential in the management of the disease. Most ...
Highlights- Models are devised to lower severe errors in predicting glucose in diabetic patients.
- Glucose forecasting models are assessed by combining clinical and numerical metrics.
- PRED-EGA methodology is used to evaluate the clinical ...
Comments