Hypertension Classification Using PPG Signals

A growing number of people throughout the world are suffering from cardiovascular disorders like hypertension. Photoplethysmography (PPG) signals are a noninvasive measurement technique that can reveal the condition of the cardiovascular system in real-time. These aspects have made the PPG a key tool for noninvasive cardiovascular health screening and detection, in addition to its affordability and ease. Based on a Synchrosqueezing Transform and a pre-trained convolutional neural network (GoogLeNet), this paper is offering an automatic classification and early diagnosis technique for hypertension utilizing PPG signals. The F1-Score of 96.83% was achieved when discriminating normotensive patients from prehypertensive and hypertensive patients. Our method outperforms all statistical metrics compared to the method using the classical time-frequency analyzing method.