An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments

TLDR

The new Internet of Things paradigm enables the design of small devices with sensing, processing, and communication capabilities that allow sensors, embedded devices, and other “things” to understand their environment. The paper proposes a distributed IoT framework for monitoring human biomedical signals during physical exertion, which can also be applied to other mobile environments requiring intensive data acquisition and high processing. The framework is implemented as a distributed IoT system and validated through a case study monitoring footballers’ heart rates during a match. The system offers flexible health computing by leveraging body‑area network resources and enables real‑time prediction of sudden death and potential injuries.

Abstract

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other 'things' ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers' heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.