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
Processes 2016, 4(4), 35; https://doi.org/10.3390/pr4040035
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)
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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Keywords:
embedded control systems; artificial pancreas; software architecture; model predictive control (MPC); safety-critical applications
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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. https://doi.org/10.3390/pr4040035
AMA Style
Zavitsanou S, Chakrabarty A, Dassau E, Doyle FJ. Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas. Processes. 2016; 4(4):35. https://doi.org/10.3390/pr4040035
Chicago/Turabian StyleZavitsanou, Stamatina; Chakrabarty, Ankush; Dassau, Eyal; Doyle, Francis J. 2016. "Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas" Processes 4, no. 4: 35. https://doi.org/10.3390/pr4040035
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