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Processes 2016, 4(4), 35; doi:10.3390/pr4040035

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

Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 , USA
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Academic Editor: B. Wayne Bequette
Received: 14 July 2016 / Revised: 14 September 2016 / Accepted: 15 September 2016 / Published: 23 September 2016
(This article belongs to the Special Issue Biomedical Systems Control)
View Full-Text   |   Download PDF [2580 KB, uploaded 29 September 2016]   |  

Abstract

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. View Full-Text
Keywords: embedded control systems; artificial pancreas; software architecture; model predictive control (MPC); safety-critical applications embedded control systems; artificial pancreas; software architecture; model predictive control (MPC); safety-critical applications
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zavitsanou, S.; Chakrabarty, A.; Dassau, E.; Doyle, F.J. Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas. Processes 2016, 4, 35.

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