An Intraoperative Glucose Control Benchmark for Formal Verification

Abstract

Diabetes associated complications are affecting an increasingly large population of hospitalized patients. Since glucose physiology is significantly impacted by patient-specific parameters, it is critical to verify that a clinical glucose control protocol is safe across a wide patient population. A safe protocol should not drive the glucose level into dangerous low (hypoglycemia) or high (hyperglycemia) ranges. Verification of glucose controllers is challenging due to the high-dimensional, non-linear glucose physiological models which contain both unobservable states and unmeasurable patient-specific parameters. This paper presents a hybrid system model of a closed-loop physiological system that includes an existing FDA-accepted high-fidelity physiological model tailored to intraoperative settings and a validated improvement to a clinical glucose control protocol for diabetic cardiac surgery patients. We propose the closed-loop model as a physiological system benchmark for verification and present our initial results on verifying the system using the SMT-based hybrid system verification tool dReach. edu).Abstract: Diabetes associated complications are affecting an increasingly large population of hospitalized patients. Since glucose physiology is significantly impacted by patient-specific parameters, it is critical to verify that a clinical glucose control protocol is safe across a wide patient population. A safe protocol should not drive the glucose level into dangerous low (hypoglycemia) or high (hyperglycemia) ranges. Verification of glucose controllers is challenging due to the high-dimensional, non-linear glucose physiological models which contain both unobservable states and unmeasurable patient-specific parameters. This paper presents a hybrid system model of a closed-loop physiological system that includes an existing FDA-accepted highfidelity physiological model tailored to intraoperative settings and a validated improvement to a clinical glucose control protocol for diabetic cardiac surgery patients. We propose the closedloop model as a physiological system benchmark for verification and present our initial results on verifying the system using the SMT-based hybrid system verification tool dReach.

Parameter Invariant Monitoring for Signal Temporal Logic

“…(2) Current human physiology models are usually parametric. This intuitively means, while there is a general agreement on the shape of a model, many of its parameters cannot be estimated by conventional techniques or it would be quite costly and/or invasive to estimate them [4,25]. Either way, these parameters, which we call nuisance parameters, may vary with time.…”

“…An explanation on how to handle error probability and indifference region is be given in Section 3.1 4. Authors in[7] introduced an algorithm for monitoring discrete time signals.…”

Formal Verification of a Multi-Basal Insulin Infusion Control Model

“…They use the dReal SMT solver [25] to find patient parameter ranges and ranges for controller gains for which a PID controller is proven to be safe with respect to specified safety properties [10]. The use of dReal SMT solver provides an exhaustive guarantee that all behaviors of the model are accounted for.…”