Pulse Oximeter Design to Predict COVID-19 Possibilities on Patient’s Health using Machine Learning

Today world is globally suffered from corona (COVID-19). Till the date no proper and effective vaccines are found that gives proper relaxation from COVID-19. Pulse oximeter is the non-invasive device that can collect data of SPO2 and Heart Rate. Based on data Machine Learning have abilities to predict the corona patient's situations. The circuitry is used for making pulse oximeter is MAX30100 MODULE, NODE MCU ESP8266 WI-FI MODULE and 16*2 JHD LCD DISPLAY. The pulse oximeter data is communicated with blynk cloud platform. This Paper mainly provide facilities to predict the patient's situations with help of ML (machine learning) algorithms. This paper provides actual values and predicted values of SPO2 and Heart Rate comparison and also predicts the values of these parameters at future time with graph. This paper mainly classifies the COVID-19 Patient's conditions on normal, at risk and critical situations. Citation: Dharmendrasinh Revar, Vedant Joshi, Jayveersinh Sevaniya. "Pulse Oximeter Design to Predict COVID-19 Possibilities on Patient's Health using Machine Learning." Global Research and Development Journal For Engineering 5.10 (2020): 9 - 14.