Executive Summary : | Diabetes is a chronic metabolic disorder caused by insufficient insulin production or ineffective use of insulin, leading to high blood glucose levels. The prevalence of diabetes has increased by 1.8% and reached 8.9% in just 10 years, with an expected rise to 134 million people by 2045. Hypertension, another lifestyle-based disease, is widespread and accounts for 63% of total deaths in India due to cardiovascular diseases. Approximately 57% of diabetic cases go undiagnosed, and only 12% of hypertension patients have their blood pressure under control. This is due to factors such as unawareness, invasiveness of the current finger-prick method, affordability, and lack of nearby healthcare centers. Existing digital healthcare gadgets lack diabetes screening capability and inaccurate BP measurements. There is a high demand for affordable, non-invasive, and personalized diabetes and BP monitoring systems using sensor and smartphone technology. This project aims to develop such systems using ubiquitous devices like smartphones, reducing regular diabetes and BP monitoring costs without burdening individuals with additional gadgets. Researchers have established the potential of photoplethysmography (PPG) signal to provide diagnostic information about both diabetes and hypertension. Efficient machine learning models will be designed to detect and display the person's diabetic and hypertension status on the smartphone screen, enabling in-home and remote diabetes and BP monitoring anytime anywhere. |