Besides the use of machine learning, signal processing techniques have also been used in combination with machine learning to estimate the health state of the user. Related to hypertension or blood pressure estimation, the most common physiological signals that have been studied to provide a constant measurement of blood pressure are electrocardiography (ECG) and Photoplethysmography (PPG), the interest in both signals have picked up certain attention in recent years due to its easy implementation on wearable devices. Moreover, ECG and PPG are commonly sampled and registered in EHRs datasets.  There are in the market a whole set of wearables devices that uses PPG Sensor to monitor oxygen levels or heart rate. The noninvasive implementation of PPG on a patient or user has motivated researchers to estimate Blood Pressure based on the PPG signal processing.