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Sensors (Basel). 2016 Mar 1;16(3):310. doi: 10.3390/s16030310.

Implementation of Context Aware e-Health Environments Based on Social Sensor Networks.

Author information

1
Electrical and Electronic Engineering Department, Public University of Navarre, Pamplona 31006, Spain. erik.aguirre@unavarra.es.
2
Electrical and Electronic Engineering Department, Public University of Navarre, Pamplona 31006, Spain. santiago.led@unavarra.es.
3
Electrical and Electronic Engineering Department, Public University of Navarre, Pamplona 31006, Spain. peio.lopez@unavarra.es.
4
School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico. leyre.azpilicueta@itesm.mx.
5
Electrical and Electronic Engineering Department, Public University of Navarre, Pamplona 31006, Spain. lserrano@unavarra.es.
6
Electrical and Electronic Engineering Department, Public University of Navarre, Pamplona 31006, Spain. francisco.falcone@unavarra.es.

Abstract

In this work, context aware scenarios applied to e-Health and m-Health in the framework of typical households (urban and rural) by means of deploying Social Sensors will be described. Interaction with end-users and social/medical staff is achieved using a multi-signal input/output device, capable of sensing and transmitting environmental, biomedical or activity signals and information with the aid of a combined Bluetooth and Mobile system platform. The devices, which play the role of Social Sensors, are implemented and tested in order to guarantee adequate service levels in terms of multiple signal processing tasks as well as robustness in relation with the use wireless transceivers and channel variability. Initial tests within a Living Lab environment have been performed in order to validate overall system operation. The results obtained show good acceptance of the proposed system both by end users as well as by medical and social staff, increasing interaction, reducing overall response time and social inclusion levels, with a compact and moderate cost solution that can readily be largely deployed.

KEYWORDS:

back office; deterministic radio planning; social sensors; wireless body area networks

PMID:
26938539
PMCID:
PMC4813885
DOI:
10.3390/s16030310
[Indexed for MEDLINE]
Free PMC Article

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