Respiratory Rate Prediction Algorithm based on Pulse Oximeter

Respiratory rate (RR) is a physiological parameter typically used to monitor patient status in clinical settings. The goal of the Respiratory Rate Prediction Project is to use supervised machine learning techniques to estimate a person’s respiratory rate using real-time, continuous Photoplethysmogram (PPG) and Electrocardiogram (ECG) and oximeter data. In addition, it is also our goal to investigate the feasibility of using such data to improve diagnostic processes in healthcare. It consists of a series of studies of different algorithms for respiratory rate estimation from clinical data and is complemented by the provision of publicly available datasets and resources.