Portable Health Monitoring Module using Machine Learning

Abstract

Amidst the current COVID-19 pandemic situation continuous health monitoring becomes important. In this work, we propose a low cost portable healthcare module which helps in tracking a patient's health conditions using various parameters such as heart rate, carbon dioxide exhalation, body temperature and electrical heart recording (ECG). This monitoring can be done autonomously without the presence of a doctor. This module is helpful in the health monitoring of patients who are in quarantine, or under treatment in a hospital. It can also be used for the health monitoring of elderly and diabled patients. We also compare some of the existing modules and draw a comparison. In addition to that we also compare different machine learning algorithms used for prediction of asthma. Our results for different algorithms have been quantified and we found that using K neighbors we got the maximum score of 87%.