Metabolic Control With the Bio-inspired Artificial Pancreas in Adults With Type 1 Diabetes

Reddy, Monika; Herrero, Pau; Sharkawy, Mohamed El; Pesl, Peter; Jugnee, Narvada; Pavitt, D.; Godsland, Ian F.; Alberti, George; Toumazou, C.; Johnston, Desmond G.; Georgiou, Pantelis; Oliver, Nick

doi:10.1177/1932296815616134

Cited by 38 publications

(32 citation statements)

References 30 publications

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“…A wearable device that integrates the CGM, CSII, a glucagon pump, the control algorithm and wireless transmitters was presented and evaluated in a pilot at home clinical study [34]. A bio-inspired AP system implemented on a miniature silicon microchip within a portable hand-held device is evaluated in [35]. In Configuration B, on the other hand, the controller is embedded directly into the pump.…”

Section: Hardware Configurations Of the Ap Systemmentioning

confidence: 99%

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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%

“…Processes 2016, 4, 35 4 of 29 B, on the other hand, the controller is embedded directly into the pump. In this case, no additional peripheral devices (such as smartphones) are required to run the control algorithm.…”

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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“…A pilot ‘at-home’ clinical study was conducted to evaluate the performance of a wearable device that integrates a Continuous Glucose Monitor (CGM), a Continuous Subcutaneous Insulin Infusion (CSII), a glucagon pump, the control algorithm and the wireless transmitters [4]. An AP system implemented on a miniature silicon microchip within a portable hand-held device is evaluated in [5]. The Medtronic hybrid closed-loop (HCL) system leverages a PID with insulin feedback (IFB) algorithm to automate basal insulin delivery while no meal is consumed.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems

Chakrabarty

Zavitsanou

Doyle

et al. 2018

IEEE Trans. Biomed. Eng.

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“…For evaluation purposes, a novel version of the clinically validated Imperial College Bio-inspired AP controller [Herrero 2012, Reddy 2014, Reddy 2015] (see Appendix A) and the UVa-Padova T1DM v3.2 system (T1DMS) simulation platform [Kovatchev 2009] were employed.…”

Section: Introductionmentioning

confidence: 99%

Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator – in silico evaluation under intra-day variability

Herrero

Bondia

Adewuyi

et al. 2017

Computer Methods and Programs in Biomedicine

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Metabolic Control With the Bio-inspired Artificial Pancreas in Adults With Type 1 Diabetes

Abstract: The BiAP is safe and achieved equivalent time in target as measured by sensor glucose, with improvement in hypoglycemia, when compared to standard pump therapy.

Cited by 38 publications

References 30 publications

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

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

Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems

Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator – in silico evaluation under intra-day variability

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