Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System.
Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System.
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DOI：
10.1109/jbhi.2015.2446413
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发表时间：
2016-01
影响因子：
7.7
通讯作者：
Cinar A
中科院分区：
文献类型：
--
作者：
Turksoy K;Samadi S;Feng J;Littlejohn E;Quinn L;Cinar A
新型的餐饮算法是根据连续的葡萄糖测量来开发的。评估算法的性能。零食。算法是一种综合的自适应人工胰腺控制系统的新模块。提出了计算方法，并使用UVA/PADOVA模拟器进行了测试。
A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman’s minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of post-prandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.