Event-triggered model predictive control for embedded artificial pancreas systems
Abstract:
The development of artificial pancreas (AP) technology for deployment in low-energy, embedded devices is contingent upon selecting an efficient control algorithm for regulating glucose in people with type 1 diabetes mellitus (T1DM). The energy consumption of the AP can be lowered by reducing updates of the control model: the number of times the decisionmaking algorithm is invoked to compute an appropriate insulin dose.
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