Abstract
Also non-diabetic patients suffer from hyperglycemia. The treatment of this non-diabetic
hyperglycemia decreases the morbidity and mortality significantly. For glucose
sensor from B. Braun which can be used for glucose monitoring in this context, parameter fitting was performed. The model is a linear diffusion FEM simulator that also models the
reaction between glucose and oxygen. A fast mathematical inversion of the simulator was carried out.
This inversion is the basis for an estimator of the glucose concentration from the signals of the real sensor. In addition the temperature dependence of
the sensor was modeled by superposition. A new estimator was constructed by using the pseudo-inverse of the
superpositions. Finally the results and possible improvements were discussed.
hyperglycemia decreases the morbidity and mortality significantly. For glucose
sensor from B. Braun which can be used for glucose monitoring in this context, parameter fitting was performed. The model is a linear diffusion FEM simulator that also models the
reaction between glucose and oxygen. A fast mathematical inversion of the simulator was carried out.
This inversion is the basis for an estimator of the glucose concentration from the signals of the real sensor. In addition the temperature dependence of
the sensor was modeled by superposition. A new estimator was constructed by using the pseudo-inverse of the
superpositions. Finally the results and possible improvements were discussed.
| Original language | English |
|---|---|
| Qualification | Master of Science |
| Awarding Institution |
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| Supervisors/Advisors |
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| Publication status | Published - 2014 |
| Externally published | Yes |
Keywords
- Diabetes
- Insulin
- GOX
- Diffusion
- FEM simulator
- estimator construction
