Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment
Diabetes is a heterogeneous group of diseases that share a common trait of elevated blood glucose levels. Insulin lowers this level by promoting glucose utilization, thus avoiding short- and long-term organ damage due to the elevated blood glucose level. A patient with diabetes uses an insulin pump...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/23/9445 |
| _version_ | 1797462107651833856 |
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| author | Martin Ubl Tomas Koutny Antonio Della Cioppa Ivanoe De Falco Ernesto Tarantino Umberto Scafuri |
| author_facet | Martin Ubl Tomas Koutny Antonio Della Cioppa Ivanoe De Falco Ernesto Tarantino Umberto Scafuri |
| author_sort | Martin Ubl |
| collection | DOAJ |
| description | Diabetes is a heterogeneous group of diseases that share a common trait of elevated blood glucose levels. Insulin lowers this level by promoting glucose utilization, thus avoiding short- and long-term organ damage due to the elevated blood glucose level. A patient with diabetes uses an insulin pump to dose insulin. The pump uses a controller to compute and dose the correct amount of insulin to keep blood glucose levels in a safe range. Insulin-pump controller development is an ongoing process aiming at fully closed-loop control. Controllers entering the market must be evaluated for safety. We propose an evaluation method that exploits an FDA-approved diabetic patient simulator. The method evaluates a Cartesian product of individual insulin-pump parameters with a fine degree of granularity. As this is a computationally intensive task, the simulator executes on a distributed cluster. We identify safe and risky combinations of insulin-pump parameter settings by applying the binomial model and decision tree to this product. As a result, we obtain a tool for insulin-pump settings and controller safety assessment. In this paper, we demonstrate the tool with the Low-Glucose Suspend and OpenAPS controllers. For average ± standard deviation, LGS and OpenAPS exhibited 1.7 ± 0.6% and 3.2 ± 1.8% of local extrema (i.e., good insulin-pump settings) out of all the entire Cartesian products, respectively. A continuous region around the best-discovered settings (i.e., the global extremum) of the insulin-pump settings spread across 4.0 ± 1.1% and 4.1 ± 1.3% of the Cartesian products, respectively. |
| first_indexed | 2024-03-09T17:31:48Z |
| format | Article |
| id | doaj.art-4832aaea84dc4988afd59a50ea4bc124 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T17:31:48Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4832aaea84dc4988afd59a50ea4bc1242023-11-24T12:14:29ZengMDPI AGSensors1424-82202022-12-012223944510.3390/s22239445Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes TreatmentMartin Ubl0Tomas Koutny1Antonio Della Cioppa2Ivanoe De Falco3Ernesto Tarantino4Umberto Scafuri5Department of Computer Science and Engineering, University of West Bohemia, Technicka 18, 330 01 Pilsen, Czech RepublicDepartment of Computer Science and Engineering, New Technologies for Information Society, University of West Bohemia, Technicka 18, 330 01 Pilsen, Czech RepublicNatural Computation Lab, Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, ItalyICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, ItalyICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, ItalyICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, ItalyDiabetes is a heterogeneous group of diseases that share a common trait of elevated blood glucose levels. Insulin lowers this level by promoting glucose utilization, thus avoiding short- and long-term organ damage due to the elevated blood glucose level. A patient with diabetes uses an insulin pump to dose insulin. The pump uses a controller to compute and dose the correct amount of insulin to keep blood glucose levels in a safe range. Insulin-pump controller development is an ongoing process aiming at fully closed-loop control. Controllers entering the market must be evaluated for safety. We propose an evaluation method that exploits an FDA-approved diabetic patient simulator. The method evaluates a Cartesian product of individual insulin-pump parameters with a fine degree of granularity. As this is a computationally intensive task, the simulator executes on a distributed cluster. We identify safe and risky combinations of insulin-pump parameter settings by applying the binomial model and decision tree to this product. As a result, we obtain a tool for insulin-pump settings and controller safety assessment. In this paper, we demonstrate the tool with the Low-Glucose Suspend and OpenAPS controllers. For average ± standard deviation, LGS and OpenAPS exhibited 1.7 ± 0.6% and 3.2 ± 1.8% of local extrema (i.e., good insulin-pump settings) out of all the entire Cartesian products, respectively. A continuous region around the best-discovered settings (i.e., the global extremum) of the insulin-pump settings spread across 4.0 ± 1.1% and 4.1 ± 1.3% of the Cartesian products, respectively.https://www.mdpi.com/1424-8220/22/23/9445diabetesinsulin pumpcontrollerin silicosmartcgms |
| spellingShingle | Martin Ubl Tomas Koutny Antonio Della Cioppa Ivanoe De Falco Ernesto Tarantino Umberto Scafuri Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment Sensors diabetes insulin pump controller in silico smartcgms |
| title | Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment |
| title_full | Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment |
| title_fullStr | Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment |
| title_full_unstemmed | Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment |
| title_short | Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment |
| title_sort | distributed assessment of virtual insulin pump settings using smartcgms and dmms r for diabetes treatment |
| topic | diabetes insulin pump controller in silico smartcgms |
| url | https://www.mdpi.com/1424-8220/22/23/9445 |
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