Outpatient Closed-Loop Control with Unannounced Moderate Exercise in Adolescents Using Zone Model Predictive Control

Huyett, Lauren M.; Ly, Trang T.; Forlenza, Gregory P.; Reuschel-DiVirgilio, Suzette; Messer, Laurel H.; Wadwa, R. Paul; Linares, Richard; Doyle, Francis J.; Pinsker, Jordan E.; Maahs, David M.; Buckingham, Bruce A.; Dassau, Eyal

doi:10.1089/dia.2016.0399

Cited by 58 publications

(45 citation statements)

References 33 publications

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“…A future design aim is that the application can be employed concurrently with other applications run by the user. To this end, a smartphone-based AP platform (currently, for the development phase of the Diabetes Assistant (DiAS) platform, the smartphone is employed as a dedicated controller, and no other phone-related functions are permitted) (DiAS; University of Virginia, Charlottesville, VA, USA) has been developed [22] and evaluated in outpatient studies [10,[23][24][25][26]. Extended studies involving a two-month evening and night closed-loop control study have also been performed [27].…”

Section: Hardware Configurations Of the Ap Systemmentioning

confidence: 99%

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

et al. 2016

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Significant increases in processing power, coupled with the miniaturization of processing units operating at low power levels, has motivated the embedding of modern control systems into medical devices. The design of such embedded decision-making strategies for medical applications is driven by multiple crucial factors, such as: (i) guaranteed safety in the presence of exogenous disturbances and unexpected system failures; (ii) constraints on computing resources; (iii) portability and longevity in terms of size and power consumption; and (iv) constraints on manufacturing and maintenance costs. Embedded control systems are especially compelling in the context of modern artificial pancreas systems (AP) used in glucose regulation for patients with type 1 diabetes mellitus (T1DM). Herein, a review of potential embedded control strategies that can be leveraged in a fully-automated and portable AP is presented. Amongst competing controllers, emphasis is provided on model predictive control (MPC), since it has been established as a very promising control strategy for glucose regulation using the AP. Challenges involved in the design, implementation and validation of safety-critical embedded model predictive controllers for the AP application are discussed in detail. Additionally, the computational expenditure inherent to MPC strategies is investigated, and a comparative study of runtime performances and storage requirements among modern quadratic programming solvers is reported for a desktop environment and a prototype hardware platform.

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Section: Hardware Configurations Of the Ap Systemmentioning

confidence: 99%

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

et al. 2016

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“…Adolescents often experience a decline in glycemic control during puberty due to hormonal changes, increased insulin resistance, and behavioral factors such as missed boluses. [5][6][7][8][9][10][11] Several recent studies have evaluated HCL systems in children and adolescents in hotel, camp, and home environments, [12][13][14][15][16][17][18][19][20][21] with results showing improved time in target range. Including all age groups in clinical studies for diabetes technology development will ensure that these systems are better able to support the needs of all people living with T1D.…”

Section: Introductionmentioning

confidence: 99%

Safety and Performance of the Omnipod Hybrid Closed-Loop System in Adults, Adolescents, and Children with Type 1 Diabetes Over 5 Days Under Free-Living Conditions

Sherr

Buckingham

Forlenza

et al. 2020

Diabetes Technology & Therapeutics

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Background: The objective of this study was to assess the safety and performance of the Omnipod Ò personalized model predictive control (MPC) algorithm in adults, adolescents, and children aged ‡6 years with type 1 diabetes (T1D) under free-living conditions using an investigational device. Materials and Methods: A 96-h hybrid closed-loop (HCL) study was conducted in a supervised hotel/rental home setting following a 7-day outpatient standard therapy (ST) phase. Eligible participants were aged 6-65 years with A1C <10.0% using insulin pump therapy or multiple daily injections. Meals during HCL were unrestricted, with boluses administered per usual routine. There was daily physical activity. The primary endpoints were percentage of time with sensor glucose <70 and ‡250 mg/dL. Results: Participants were 11 adults, 10 adolescents, and 15 children aged (meanstandard deviation) 28.8 -7.9, 14.3 -1.3, and 9.9 -1.0 years, respectively. Percentage time ‡250 mg/dL during HCL was 4.5% -4.2%, 3.5% -5.0%, and 8.6% -8.8% per respective age group, a 1.6-, 3.4-, and 2.0-fold reduction compared to ST (P = 0.1, P = 0.02, and P = 0.03). Percentage time <70 mg/dL during HCL was 1.9% -1.3%, 2.5% -2.0%, and 2.2% -1.9%, a statistically significant decrease in adults when compared to ST (P = 0.005, P = 0.3, and P = 0.3). Percentage time 70-180 mg/dL increased during HCL compared to ST, reaching significance for adolescents and children: HCL 73.7% -7.5% vs. ST 68.0% -15.6% for adults (P = 0.08), HCL 79.0% -12.6% vs. ST 60.6% -13.4% for adolescents (P = 0.01), and HCL 69.2% -13.5% vs. ST 54.9% -12.9% for children (P = 0.003). Conclusions: The Omnipod personalized MPC algorithm was safe and performed well over 5 days and 4 nights of use by a cohort of participants ranging from youth aged ‡6 years to adults with T1D under supervised freeliving conditions with challenges, including daily physical activity and unrestricted meals.

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“…Similar zone-MPC systems have been tested in the past in several clinical trials (16,28–30). Huyett et al (28) investigated zone-MPC as a hybrid AP system in 10 adolescents during a 72-h supervised hotel stay.…”

Section: Discussionmentioning

confidence: 99%

“…Huyett et al (28) investigated zone-MPC as a hybrid AP system in 10 adolescents during a 72-h supervised hotel stay. In that study, the mean glucose value (150 ± 19 mg/dL) and percent time in target range 70–180 mg/dL (71 ± 10%) were very similar to the results from this trial, whereas the percent time <70 mg/dL (2.5 ± 1.8%) was slightly higher than for this trial.…”

Section: Discussionmentioning

confidence: 99%

Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial

Forlenza

Deshpande

et al. 2017

Diabetes Care

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OBJECTIVEAs artificial pancreas (AP) becomes standard of care, consideration of extended use of insulin infusion sets (IIS) and continuous glucose monitors (CGMs) becomes vital. We conducted an outpatient randomized crossover study to test the safety and efficacy of a zone model predictive control (zone-MPC)–based AP system versus sensor augmented pump (SAP) therapy in which IIS and CGM failures were provoked via extended wear to 7 and 21 days, respectively.RESEARCH DESIGN AND METHODSA smartphone-based AP system was used by 19 adults (median age 23 years [IQR 10], mean 8.0 ± 1.7% HbA1c) over 2 weeks and compared with SAP therapy for 2 weeks in a crossover, unblinded outpatient study with remote monitoring in both study arms.RESULTSAP improved percent time 70–140 mg/dL (48.1 vs. 39.2%; P = 0.016) and time 70–180 mg/dL (71.6 vs. 65.2%; P = 0.008) and decreased median glucose (141 vs. 153 mg/dL; P = 0.036) and glycemic variability (SD 52 vs. 55 mg/dL; P = 0.044) while decreasing percent time <70 mg/dL (1.3 vs. 2.7%; P = 0.001). AP also improved overnight control, as measured by mean glucose at 0600 h (140 vs. 158 mg/dL; P = 0.02). IIS failures (1.26 ± 1.44 vs. 0.78 ± 0.78 events; P = 0.13) and sensor failures (0.84 ± 0.6 vs. 1.1 ± 0.73 events; P = 0.25) were similar between AP and SAP arms. Higher percent time in closed loop was associated with better glycemic outcomes.CONCLUSIONSZone-MPC significantly and safely improved glycemic control in a home-use environment despite prolonged CGM and IIS wear. This project represents the first home-use AP study attempting to provoke and detect component failure while successfully maintaining safety and effective glucose control.

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Outpatient Closed-Loop Control with Unannounced Moderate Exercise in Adolescents Using Zone Model Predictive Control

Abstract: The use of the ZMPC+HMS algorithms is feasible in the adolescent outpatient environment and achieved significantly more time in the desired glycemic range than SAP in the face of unannounced exercise and large announced meal challenges.

Cited by 58 publications

References 33 publications

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

Safety and Performance of the Omnipod Hybrid Closed-Loop System in Adults, Adolescents, and Children with Type 1 Diabetes Over 5 Days Under Free-Living Conditions

Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial

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