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Performance Analysis of Different Embedded Systems and Open-Source Optimization Packages Towards an Impulsive MPC
Jhon E Goez-Mora1, María F Villa-Tamayo1, Monica Vallejo1
1Grupo GITA, Facultad de Minas, Universidad Nacional de Colombia, Medellín, Colombia.
Frontiers in Endocrinology
|May 13, 2021
Summary
Researchers evaluated embedded systems and algorithms for artificial pancreas control in type 1 diabetes (T1D). The Quadprog solver and Raspberry Pi 3/Tinker Board S platforms showed promise for portable glucose regulation devices.
Area of Science:
- Biomedical Engineering
- Control Systems Engineering
- Computer Science
Background:
- Artificial pancreas technology aims for safe, portable, and efficient glucose regulation for type 1 diabetes (T1D).
- Model Predictive Control (MPC) is a leading strategy for T1D glucose control but often developed in computer environments, posing challenges for portable implementation.
Purpose of the Study:
- To assess the performance of various embedded platforms and open-source optimization solvers for implementing MPC-based artificial pancreas systems.
- To identify the most suitable hardware and software combinations for safe and efficient T1D management in a portable setting.
Main Methods:
- Evaluated six embedded platforms and three open-source optimization solvers using four MPC formulations of increasing complexity.
- Employed a hardware-in-the-loop methodology to simulate glucose control in virtual adult subjects with T1D.
- Compared performance based on execution time, deviation from MATLAB simulations, processor temperature, energy consumption, time in normoglycemia, and hypo-/hyperglycemic events.
Main Results:
- The Quadprog solver demonstrated the highest fidelity in replicating control strategies developed in MATLAB.
- Raspberry Pi 3 and Tinker Board S were identified as suitable embedded systems for portable artificial pancreas applications based on the evaluated criteria.
- Performance metrics including execution time, energy consumption, and glucose control accuracy were systematically compared across different configurations.
Conclusions:
- Quadprog is recommended for its accuracy in implementing MPC for T1D glucose control on embedded systems.
- Raspberry Pi 3 and Tinker Board S offer a viable foundation for developing portable artificial pancreas devices.
- This study provides crucial insights for the practical realization of advanced T1D management technologies.
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