Descripción
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This paper describes the design and evaluation of a mobile software library, HealthTracker, which aims to produce activity and energy expenditure estimations in real-time from accelerometer and gyroscope data provided by wearable sensors. Using feature extraction together with a classifier trained using machine learning, the system will automatically and periodically send all the produced estimations to a cloud-based platform that will allow later evaluation by both the user and a physician or caretaker. The system is presented within the DAPHNE platform, an ICT ecosystem designed to provide a means for remote health and lifestyle monitoring and guidance between physicians and their patients. | |
Internacional
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Si |
Nombre congreso
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International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare |
Tipo de participación
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960 |
Lugar del congreso
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Revisores
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Si |
ISBN o ISSN
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1877-0509 |
DOI
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Fecha inicio congreso
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19/09/2016 |
Fecha fin congreso
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22/09/2016 |
Desde la página
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348 |
Hasta la página
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355 |
Título de las actas
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International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare ICTH2016 |