Glucose Regulation for Subjects with Type 1 Diabetes Using Active Disturbance Rejection Control

Cai, Deheng; Song, Jiliang; Wang, Junzheng; Shi, Dawei

doi:10.23919/chicc.2019.8866391

Cited by 3 publications

(2 citation statements)

References 34 publications

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“…Cai et al [20] proposed a method based on the active disturbance rejection control (ADRC) for regulation of BG levels by adding the insulin on board (IOB) and insulin delivery constraints to ensure the safety of the control algorithm. The proposed ADRC controller is composed of two modules: the ADRC module (composed of tracking differentiator (TD), extended state observer (ESO), and nonlinear feedback) and the constraints module (composed of the IOB, non-negative, and maximum input constraints).…”

Section: E Active Disturbance Rejection Control Approachmentioning

confidence: 99%

Review of Algorithms for Improving Control of Blood Glucose Levels

Tasic

Eigner

Kovács

2020

2020 IEEE 18th International Symposium on Intelligent Systems and Informatics (SISY)

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In this study, we review recently proposed advanced methods based on various techniques in order to improve blood glucose control while avoiding an increased risk of hypoglycemia or hyperglycemia in patients with type 1 diabetes. We introduce type 1 diabetes and the artificial pancreas and provide an overview of research advances based on predictive control, statistical processes, filters, and machine learning. Common control methods have been successfully used to control blood glucose levels while new approaches that rely on machine learning algorithms offer promising performance.Index Terms-Type 1 diabetes, artificial pancreas, continuous glucose monitoring, model predictive control, PID control, Kalman filter, neural networks, machine learning

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Section: E Active Disturbance Rejection Control Approachmentioning

confidence: 99%

Review of Algorithms for Improving Control of Blood Glucose Levels

Tasic

Eigner

Kovács

2020

2020 IEEE 18th International Symposium on Intelligent Systems and Informatics (SISY)

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“…However, some studies have found that the experience and views of using CSII therapy and CGM is mixed which might be related to the accuracy, frequent annoyances from alarms, insertion pain and the interruption to the daily life of users (Brew‐Sam et al., 2021 ; Messer et al., 2018 ). Notably, such advanced diabetes technology is only used in clinical research in China (Cai et al., 2019 ; Wu et al., 2020 ). Thus, most Chinese studies focus on the effectiveness and safety of the combined use of CSII therapy and CGM in adult population, also including some children and adolescents (Dai et al., 2018 ; Wu et al., 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Parents' experiences on the combined use of continuous subcutaneous insulin infusion and real‐time continuous glucose monitoring to manage Type 1 diabetes in their children: A systematic review and meta‐synthesis of qualitative studies

Luo

Pan

et al. 2021

Nursing Open

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The incidence of Type 1 diabetes (T1DM) has increased significantly in many countries worldwide (Manuwald et al., 2017). Although there was a lower incidence of T1DM in Chinese children, the incidence amongst children under 15 has been rising dramatically over the past two decades (Weng et al., 2018). It is estimated that there are over 4,000 new cases of T1DM in children annually in China (Weng et al., 2018). Without appropriate insulin treatment and optimal glycaemic control, the condition of children with T1DM can exacerbate rapidly within 24 hr, resulting in diabetic ketoacidosis (DKA), permanent disability or even death (Cavan, 2018). Optimal diabetes management are important for children and adolescents with T1DM.

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