Healthcare IoT

Abstract

The interaction between technology and healthcare has a long history. However, recent years have witnessed the quick growth and appropriation of the Internet of Things (IoT) paradigm, the advent of miniature wearable biosensors, and research advances in Big Data techniques for effective manipulation of large, multiscale, multimodal, distributed, and heterogeneous data sets. This advancement has created new opportunities in customized healthcare services. The IoT has signaled a paradigm change on the horizon for healthcare, bringing advantages such as accessibility, availability, personalized content, and cost-efficient delivery. While Healthcare IoT has greatly increased the number of possibilities for meeting healthcare needs, there are still several challenges that must be addressed in order to create adaptable, appropriate, power-efficient, and safe systems that address health needs. Empowering this transformation will require the software and hardware communities to come together to achieve extensive technological advancements. This chapter addresses all these important aspects of novel IoT technologies for smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and Big Data analytics. It identifies new perspectives and highlights compelling research issues and challenges such as scalability, interoperability, device-network-human interfaces, and security. Finally, the feasibility of healthcare IoT is investigated by a novel case study, ECG-based arrhythmia detection, based on deep learning and convolutional neural network (CNN) methods distributed across Edge-Fog-Cloud.