Cardiovascular Diseases Detection Using Photo Plethysmography (PPG) Signal Data - Padmavathi, Y.; Ushasree, R.; Chitra, Batumalai (INTI International University, 2024)
Photoplethysmography (PPG) signals have been widely used in clinical practice as diagnostic tools. In this article, techniques of machine learning have been used to improve the detection of cardiovascular disease (CVD) from the PPG signal data. Hypertension and stress are the main causes of the increase in blood pressure (BP), which in turn causes cardiovascular diseases. The treatment of patients, mainly those who have been suffering from CVD, resulted in an increment in the death rate. PPG is non-invasive, low-cost, fast, and simple to use. The signals of PPG are used for figuring out the anomalies in the cardiovascular system. By using PPG technology, cardiovascular parameters like blood pressure and heart rate are detected. This article investigates a machine learning and Deep Learning technique, which is Neural Network (NN), that has been used to assist physicians, this has achieved an accuracy of 98% by using the PPG-BP data set.