Development and Implementation of a Blood Glucose Index Determination System Using Non-Invasive Methods

This project addresses the critical need for frequent blood glucose monitoring in diabetic patients, as poor management of this metabolic condition leads to severe complications. Diabetes, characterized by glucose levels fluctuating outside the normal range (90-120 mg/dL), affects millions globally. The primary goal is to overcome the limitations of current invasive methods by developing a non-invasive solution. The methodology employed is investigative, based on analysis-synthesis and induction-deduction. The approach involves an exhaustive evaluation of existing non-invasive methods and the application of machine learning techniques for glucose detection. The process culminates with the programming of an algorithm, its rigorous comparison against traditional methods, its implementation in a continuous monitoring device, and comprehensive testing of the system against commercially available devices to validate its efficacy and improve the quality of life for diabetic individuals.<br/><br/><b>Goal</b>: <br/>To develop and implement a system for determining blood glucose levels using non-invasive methods.<br/><br/><b>Research lines</b>: <br/>Control engineering and automation technologies