Program

Stephen Mackintosh

LifeScan Scotland

The Mathematical Modeling of Electrochemical Blood Glucose Sensors

Presented with Steve Blythe

Our work involves the modeling of a basic blood glucose sensor, a device whose function is the measurement of a patient's blood sugar levels. We show how the basic behavior of such systems can be modeled analytically with partial differential equations, and how this quickly requires numerical solutions when more complexity is introduced to species interactions and domain geometry, necessitating the use of numerical solvers like COMSOL Multiphysics. We further demonstrate how such models can be powerful tools in the subsequent development of device algorithms that attempt to maximize the glucose signal from the sensor whilst mitigating undesirable error from interferences in the blood sample. In particular we look at Uric acid as a case study, a species present in human blood, which can generate unwanted background noise in an electrochemical sensor.

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