Return to search

Glucose Sensing and Differentiating Systems with Organic Electrochemical Neurons : A Future Outlook for Type 2 Diabetes / Detektion och urskiljning av glukoshalter med organiska elektrokemiska neuroner

In recent years great advances in the field of biomedical engineering and organic electronics have been achieved. One promising application would be the regulation of blood glucose concentration in type 2 diabetes patients. This application would eliminate medication and would improve the standard of life. To achieve this goal a system is needed which receives information about the glucose concentration and reacts upon it. This output reaction could then be used to stimulate the body's own glucose regulation mechanisms. This thesis combined a glucose sensor with an artificial neuron to take the first step towards such a system. Two different artificial neurons, the Axon-Hillock neuron and the astable multivibrator, were characterized and examined upon their usability. The Axon-Hillock, build with organic electrochemical transistors, revealed that it could be applied for both regulating high and low blood glucose concentrations. The astable multivibrator, build with silicon-based transistors, was not as functional as the Axon-Hillock neuron but with more development it could become as good. The placement of the glucose sensor in the astable multivibrator circuit is essential parameter to consider. The results demonstrate that the examined system is functional and could become a part of a larger closed-loop system. Future tests on an animal model may demonstrate its viability as a treatment for type 2 diabetes.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-200712
Date January 2024
CreatorsZiske, Sophie
PublisherLinköpings universitet, Institutionen för teknik och naturvetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

Page generated in 0.0091 seconds