Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques

摘要

ObjectiveThis work presents a system for a simultaneous non-invasive estimate of the blood glucose level (BGL) and the systolic (SBP) and diastolic (DBP) blood pressure, using a photoplethysmograph (PPG) and machine learning techniques. The method is independent of the person whose values are being measured and does not need calibration over time or subjects.