Non-Invasive Blood Glucose Monitoring using ECG Signal

As a chronic metabolic disease, diabetes mellitus need ongoing blood glucose monitoring. The invasive nature of traditional blood glucose monitoring methods, which require finger pricks might make patients uncomfortable and reduce their compliance. As alternatives, non-invasive technique shave attracted a lot of interest recently, with electrocardiogram (ECG)-based glucose monitoring showing promise. The possibility of estimating blood glucose levels without invasive methods using ECG signals are explored to study. Changes the heart rate variability (HRV) and the shape of the ECG waveform are two examples of how physiological changes brought on by variations in glucose concentration are known to be reflected in ECG signals. Features are taken from the ECG signals and linked to the associated glucose levels using sophisticated signal processing techniques and machine learning algorithms. This method offers a continuous, real-time, and painless monitoring option. The initial findings show a strong relationship between blood glucose levels and ECGderived characteristics, suggesting that ECG may be used as a stand-in marker for glucose monitoring. The goal of this effort is to improves the development of non-invasive, wearable glucose monitoring device that can help patient control their diabetes and live better lives.