Statistical physics approaches for network-on-chip traffic characterization
CODES+ISSS '09 Proceedings of the 7th IEEE/ACM international conference on Hardware/software codesign and system synthesis
Feedforward-feedback multiple predictive controllers for glucose regulation in type 1 diabetes
Computer Methods and Programs in Biomedicine
An FPGA implementation of a sparse quadratic programming solver for constrained predictive control
Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays
A new general glucose homeostatic model using a proportional-integral-derivative controller
Computer Methods and Programs in Biomedicine
Towards a Science of Cyber-Physical Systems Design
ICCPS '11 Proceedings of the 2011 IEEE/ACM Second International Conference on Cyber-Physical Systems
Cyberphysical Systems: Workload Modeling and Design Optimization
IEEE Design & Test
IEEE Transactions on Information Technology in Biomedicine
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
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Healthcare costs in the US are among the highest in the world. Widespread chronic diseases such as diabetes constitute a significant cause of rising healthcare costs. Despite the increased need for smart healthcare systems that monitor patients' body balance, there is no coherent theory that facilitates the design and optimization of efficient and robust cyber physical systems. In this paper, we propose a mathematical model for capturing the dynamics of blood glucose characteristics (e.g., time dependent fractal behavior) observed in real world measurements via fractional calculus concepts. Building on our time dependent fractal model, we propose a novel mathematical model as well as hardware architecture for an artificial pancreas that relies on solving a constrained multi-fractal optimal control problem for regulating insulin injection. We verify the accuracy of our mathematical model by comparing it to conventional nonfractal models using real world measurements and showing that the nonlinear optimal controller based on fractal calculus concepts is superior to nonfractal controllers. We also verified the feasibility of in silico realization of the proposed optimal control algorithm by prototyping on FPGA platform.