Next Article in Journal
A Review on the Dissection of Quenched Blast Furnaces—Spanning from the Early 1950s to the 1970s
Next Article in Special Issue
Algorithms for a Single Hormone Closed-Loop Artificial Pancreas: Challenges Pertinent to Chemical Process Operations and Control
Previous Article in Journal
Operator Training Simulator for an Industrial Bioethanol Plant
Previous Article in Special Issue
Discrete Blood Glucose Control in Diabetic Göttingen Minipigs
Open AccessFeature PaperReview

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
*
Author to whom correspondence should be addressed.
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. 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
Show Figures

Graphical abstract

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 Style

Zavitsanou, 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

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop