Data Analysis Methods for Health Monitoring Sensors: A survey

Abstract

Innovations in health monitoring systems are fundamental for the continuous improvement of remote healthcare. With the current presence of SARS-CoV-2, better known as COVID-19, in people’s daily lives, solutions for monitoring heart and especially respiration and pulmonary functions are more needed than ever. In this paper, we survey the current approaches that utilize the advantages of sensor technologies to sense, analyze, and estimate health data related to respiration, heart, and sleep monitoring. We focus on illustrating the signal processing and machine learning techniques used on each approach to facilitate researchers’ understanding of how data is processed nowadays. We have classified the reviewed papers into two main categories: contact and contactless sensors. In each category, we discuss the different types of used sensors, the data analysis technique, and the accuracy of those techniques.