Online Glucose Prediction Using Computationally Efficient Sparse Kernel Filtering Algorithms in Type-1 Diabetes

Streaming data from continuous glucose monitoring (CGM) systems enable the recursive identification of models to improve estimation accuracy for effective predictive glycemic control in patients with type-1 diabetes. A drawback of conventional recursive identification techniques is the increase in c...

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Опубликовано в: :IEEE Trans Control Syst Technol
Главные авторы: Yu, Xia, Rashid, Mudassir, Feng, Jianyuan, Hobbs, Nicole, Hajizadeh, Iman, Samadi, Sediqeh, Sevil, Mert, Lazaro, Caterina, Maloney, Zacharie, Littlejohn, Elizabeth, Quinn, Laurie, Cinar, Ali
Формат: Artigo
Язык:Inglês
Опубликовано: 2018
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Article
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC7375403/
https://ncbi.nlm.nih.gov/pubmed/32699492
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/tcst.2018.2843785
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