ArticleJournal of diabetes science and technology2022
Efficient Closed Loop Simulation of Do-It-Yourself Artificial Pancreas Systems.
Article in Journal of diabetes science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Recent advances in the precision control strategy of artificial pancreas.Medical & biological engineering & computing · 2024Review
- Article
- Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility.Journal of diabetes science and technology · 2023Review
- Closing the loop for patients with Parkinson disease: where are we?Nature reviews. Neurology · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNumerical simulations, also referred to as in silico trials, are nowadays the first step toward approval of new artificial pancreas (AP) systems. One suitable tool to run such simulations is the UVA/Padova Type 1 Diabetes Metabolic Simulator (T1DMS). It was used by Toffanin et al. to provide data about safety and efficacy of AndroidAPS, one of the most wide-spread do-it-yourself AP systems. However, the setup suffered from slow simulation speed. The objective of this work is to speed up simulation by implementing the algorithm directly in MATLAB
methodFirstly, AndroidAPS is re-implemented in MATLAB
resultsUnit tests and integration tests proved the equivalence of the new implementation and the original AndroidAPS code. Simulation of the scenario required approximately 15 minutes, corresponding to a speed-up factor of roughly 1000 with respect to real time. The results closely resemble those presented by Toffanin et al. Discrepancies were to be expected because a different virtual population was considered. Also, some parameters could not be extracted from and harmonized with the original setup.
conclusionsThe new implementation facilitates extensive in silico trials of AndroidAPS due to the significant reduction of runtime. This provides a cheap and fast means to test new versions of the algorithm before they are shared with the community.
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