A Non-invasive PPG-based Blood Glucose Measurement using an Optical Sensor and Optimized Machine Learning Algorithm

SignalMed is developing a non-invasive blood glucose monitoring solution using a novel AI-enhanced photoplethysmography (PPG) algorithm. Grounded in robust biomedical research, this method captures PPG signals and combines them with user health metrics to estimate blood glucose levels without the need for finger pricks. The AI algorithms processed the data in real time, enabling accurate glucose level estimation and classification, offering comparable accuracy to contemporary methods.