IoT for Better Mobile Health Applications

Abstract

Using big data in health is booming. Recently, several novel innovations and techniques applying big data to Bioinformatics and health research are released. Nowadays, devices such as smartphones, sensors; individuals like patients, healthcare professionals, or investigators and collective entities such as healthcare facilities and institutions are regularly creating and collecting a vast quantity of health data that can diagnose and treat new disorders. The genuine dilemma in applying mobile health is how to identify, collect, analyze, and distribute information to make better and simpler lives for individuals via early predicting risk factors. For instance, researchers have built many techniques to enable managing chronic diseases. Medical devices for ongoing monitoring health indicators or detecting timely online healthcare data like patient self-administering physical therapy are greatly needed. Today, for accessing high-speed internet connections on mobile phones, several smart patients are using smartphone applications (apps) to monitor routinely various daily health demands. Such smartphone apps and devices are increasingly utilized and embedded with e-health and telemedicine through the Internet of Things (IoT). However, confidentiality and safety are major concerns that require cooperation with policymakers and prompt communication of potential hazards. This work examines the applications of the IoT and m-health in healthcare. It also describes innovative methods for improving health via computational technologies and techniques for integrating IoT and m-health, including a proposed model for diabetes self-management.