GLASS: Glucose Level Measuring via Breathe Acetone Sensing through Laser Spectroscopy
By Akul, Rohith
The proposed research aims to develop a laser spectroscopy analyzer that leverages classical machine-learning algorithms to analyze laser spectra for the detection of glucose levels and sensitivity in breath samples. This innovative approach seeks to emulate the functionality of a breathalyzer while providing a non-invasive method for monitoring metabolic health. Our hypothesis is that the analyzer will effectively distinguish and quantify specific spectral signatures associated with acetone levels in breath, allowing for an accurate assessment of glucose sensitivity through advanced data processing techniques. We are currently developing our drying mechanism and multi-pass gas chamber to establish laser spectra from breathing and analyze acetone content.