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Ambient intelligence systems for personalized sport training

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Identifiers
URI: http://hdl.handle.net/10317/1631
ISSN: 1424-8220
DOI: 10.3390/s100302359
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Author
Vales Alonso, Javier; López Matencio Pérez, Pablo Antonio; González Castaño, Francisco Javier; Navarro Hellín, Honorio; Baños Guirao, Pedro José; [et al.]
Research Group
Grupo Ingeniería Telemática (GIT)
Knowledge Area
Ingeniería Telemática
Sponsors
This work has been supported by grants DEP2006-56158-C03-01/02/03, TEC2007-67966 -01/02/TCM CON-PARTE-1/2 (Ministerio de Educacion y Ciencia, Spain), TSI-020301-2008-16 ELISA and TSI-020301-2008-2 PIRAmIDE (Ministerio de Industria, Turismo y Comercio, Spain), and it has been also developed within the framework of “Programa de Ayudas a Grupos de Excelencia de la Region de Murcia”, funded by Fundacion Seneca, Agencia de Ciencia y Tecnologia de la Region de Murcia (Plan Regional de Ciencia y Tecnologia 2007/2010).
Publication date
2010-03-22
Publisher
MDPI AG
Bibliographic Citation
VALES ALONSO, Javier, LÓPEZ MATENCIO, Pablo, GONZÁLEZ CASTAÑO. Francisco, NAVARRO HELLÍN, Honorio, BAÑOS GUIRAO, Pedro J., PÉREZ MARTÍNEZ, Francisco J., MARTÍNEZ ÁLVAREZ, Rafael, P., GONZÁLEZ JIMÉNEZ, Daniel, GIL CASTIÑEIRA, Daniel, DURO FERNÁNDEZ, Richard. Ambient intelligence systems for personalized sport training. Sensors, 10: 2359-2385, Marzo 2010. ISSN 1424-8220
Peer review
si
Keywords
Inteligencia ambiental
Servicios contextuales
Red de sensor inalámbrico
Entrenamiento deportivo
Aprendizaje automático
Ambient intelligence (AmI)
Contextual services
Wireless sensor network
Sport training
Machine learning
Abstract
Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, ...
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