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Sensors 2017, 17(10), 2302; https://doi.org/10.3390/s17102302

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

1
Department of Computer Science Technology and Computation, University of Alicante, 03690 Alicante, Spain
2
Department of Software and Computing Systems, University of Alicante, 03690 Alicante, Spain
3
Department of Computer Systems Architecture, Gdansk University of Technology, 80-233 Gdansk, Poland
*
Author to whom correspondence should be addressed.
Received: 7 August 2017 / Revised: 4 October 2017 / Accepted: 5 October 2017 / Published: 10 October 2017
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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. View Full-Text
Keywords: Internet of Things; healthcare monitoring; wearable sensing; sensor network; case studies Internet of Things; healthcare monitoring; wearable sensing; sensor network; case studies
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Mora, H.; Gil, D.; Terol, R.M.; Azorín, J.; Szymanski, J. An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments. Sensors 2017, 17, 2302.

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