Journal Article

A modular safety system for an insulin dose recommender: A feasibility study


Background: Delivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin dose recommender platform developed within the EU-funded PEPPER project. Methods: The proposed safety system is composed of four modules which use a novel glucose forecasting algorithm. These modules are: predictive glucose alerts and alarms; a predictive low-glucose basal insulin suspension module; an advanced rescue carbohydrate recommender for resolving hypoglycaemia; and a personalised safety constraint applied to insulin recommendations. The technical feasibility of the proposed safety system was evaluated in a pilot study including eight adult subjects with type 1 diabetes on multiple daily injections over a duration of six weeks. Glycaemic control and safety system functioning were compared between the two-weeks run-in period and the end-point at eight weeks. A standard insulin bolus calculator was employed to recommend insulin doses. Results: Overall, glycaemic control improved over the evaluated period. In particular, percentage time in the hypoglycaemia range (<3.0mmol/l) significantly decreased from 0.82 (0.05-4.79) % at run-in to 0.33 (0.00-0.93) % at endpoint (p=0.02). This was associated with a significant increase in percentage time in target range (3.9-10.0mmol/l) from 52.8 (38.3-61.5) % to 61.3 (47.5-71.7) % (p=0.03). There was also a reduction in number of carbohydrate recommendations. Conclusion: A safety system for an insulin dose recommender has been proven to be a viable solution to reduce the number of adverse events associated to glucose control in type 1 diabetes.

Attached files


Liu, Chengyuan
Avari, Parizad
Leal, Yenny
Wos, Marzena
Sivasithamparam, Kumuthine
Georgiou, Pantelis
Reddy, Monika
Fernández-Real, José Manuel
Martin, Clare
Fernández-Balsells, Mercedes
Oliver, Nick
Herrero, Pau

Oxford Brookes departments

Faculty of Technology, Design and Environment\School of Engineering, Computing and Mathematics


Year of publication: 2019
Date of RADAR deposit: 2019-05-22

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