Abstract
The non-invasive monitoring of blood glucose and creatinine concentrations is crucial for managing diabetes and chronic kidney disease. This thesis explores the development of a novel wearable biosensor for simultaneous and non-invasive measurement of these blood components. The research focused on absorption spectroscopy as the detection method and a wearable device for convenient monitoring.A concept for the bio-sensor using near-infrared light and absorption spectroscopy was established. The appropriate components of the wearable bio-sensor were chosen. Machine learning models for blood component estimation based on light-tissue interaction was proposed. As well as a functional PCB design for the bio-sensor was developed.
This research has laid a strong foundation for a groundbreaking wearable biosensor for non-invasive blood component monitoring, potentially offering a more convenient and comfortable approach for managing diabetes and chronic kidney disease.
| Date of Award | 14 May 2024 |
|---|---|
| Original language | American English |
| Supervisor | Jelinek (Supervisor) |
Keywords
- Continuous Glucose Monitor
- Biosensor
- CKD
- Diabetes
- Monte Carlo Simulation
- Machine Learning
- NIR
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