Adaptive Control of Artificial Pancreas Systems - A Review
Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-d...
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Online Access: | http://dx.doi.org/10.1260/2040-2295.5.1.1 |
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doaj-83a4b72eda794e6f9abb6d27ff4c6a312020-11-24T20:54:31ZengHindawi LimitedJournal of Healthcare Engineering2040-22952014-01-015112210.1260/2040-2295.5.1.1Adaptive Control of Artificial Pancreas Systems - A ReviewKamuran Turksoy0Ali Cinar1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USADepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USAArtificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.http://dx.doi.org/10.1260/2040-2295.5.1.1 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kamuran Turksoy Ali Cinar |
spellingShingle |
Kamuran Turksoy Ali Cinar Adaptive Control of Artificial Pancreas Systems - A Review Journal of Healthcare Engineering |
author_facet |
Kamuran Turksoy Ali Cinar |
author_sort |
Kamuran Turksoy |
title |
Adaptive Control of Artificial Pancreas Systems - A Review |
title_short |
Adaptive Control of Artificial Pancreas Systems - A Review |
title_full |
Adaptive Control of Artificial Pancreas Systems - A Review |
title_fullStr |
Adaptive Control of Artificial Pancreas Systems - A Review |
title_full_unstemmed |
Adaptive Control of Artificial Pancreas Systems - A Review |
title_sort |
adaptive control of artificial pancreas systems - a review |
publisher |
Hindawi Limited |
series |
Journal of Healthcare Engineering |
issn |
2040-2295 |
publishDate |
2014-01-01 |
description |
Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes. |
url |
http://dx.doi.org/10.1260/2040-2295.5.1.1 |
work_keys_str_mv |
AT kamuranturksoy adaptivecontrolofartificialpancreassystemsareview AT alicinar adaptivecontrolofartificialpancreassystemsareview |
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1716794296123785216 |