Electrocardiogram Pulse Wave Analysis for Holistic Cardiovascular Assessment

This paper introduces an innovative approach to non-invasive heart health assessment by integrating pulse data obtained from the human wrist with machine learning techniques. Drawing inspiration from ancient Ayurvedic techniques like Nadi Pariksha, we analyze pulse characteristics such as shape, intensity, and frequency to deduce potential health conditions, offering tailored treatment approaches. Employing portable pulse data capturing instruments in non-hospital settings, we relay the collected data to a model of machine learning that applies pattern analysis for classifying health conditions. By extrapolating insights from diverse datasets, we enhance the accuracy and applicability of our model's classifications.