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Escolar J.R.,Fundacion CTIC Centro Tecnologico
EICS 2013 - Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems | Year: 2013

Model-Based User Interface Design (MBUID) consists of a step-wise method that structures the development of User Interfaces (UIs) based on models. According to this method, developers focus on creating a UI model, that is an abstract representation of it, and delegate the UI code generation process to automatic tools that take into account platform peculiarities. This paper explores the applicability of MBUI techniques to context-aware Service Front Ends (SFEs), i.e. UIs of web services that react to context changes. For this purpose, it introduces a context-aware dialog model that captures the adaptable behavior of a UI depending on variations of the context of use, a standard-based notation to represent it, and an open-source development environment that supports this development method. Copyright © 2013 ACM. Source


Carus J.L.,Fundacion CTIC Centro Tecnologico | Garcia S.,Fundacion CTIC Centro Tecnologico | Garcia R.,Fundacion CTIC Centro Tecnologico | Waterworth J.,UmeaUniversity | Erdt S.,Innovationsmanufaktur GmbH
Studies in Health Technology and Informatics | Year: 2014

The ELF@Home project is a research and innovation project running from June 1st 2013 to May 31st 2016 and co-funded by the Ambient Assisted Living Joint Programme (AAL JP) and National Authorities in Spain, Sweden and Germany. The ELF@Home project relies on the use of the proven advantages of elderly fitness to develop a self-care solution based on self-check of health conditions and self-fitness at home. The project uses information and communication technologies (ICT) to build an autonomous fitness system targeting healthy or pre-frail elderly people aged over 65 and living independently at home. © 2014 The authors and IOS Press. All rights reserved. Source


Carus J.L.,Fundacion CTIC Centro Tecnologico | Pelaez V.,Fundacion CTIC Centro Tecnologico | Lopez G.,Fundacion CTIC Centro Tecnologico | Fernandez M.A.,Fundacion CTIC Centro Tecnologico | And 2 more authors.
Studies in Health Technology and Informatics | Year: 2013

Abnormal human behavior detection under free-living conditions is a reliable technique to detect activity disorders and diseases. This work proposes an acceleration-based algorithm to detect abnormal behavior as an abnormal increase or decrease in physical activity (PA). The algorithm is based on statistical features of human physical activity. Using a period of observed physical activity as a reference, the algorithm is able to detect abnormal behavior in other periods of time. The approach is unsupervised as the modeling of the reference behavior is not required. It has been validated with a group of 12 users under free-living conditions for two days. Results show a precision greater than 75% and a recall of 92%. © 2013 The authors and IOS Press. All rights reserved. Source


Carus Candas J.L.,Fundacion CTIC Centro Tecnologico | Pelaez V.,Fundacion CTIC Centro Tecnologico | Lopez G.,Fundacion CTIC Centro Tecnologico | Fernandez M.A.,Fundacion CTIC Centro Tecnologico | And 2 more authors.
Pervasive and Mobile Computing | Year: 2014

Abnormal human behaviour detection under free-living conditions is a reliable method to detect disorders and diseases in healthcare applications. The problem with current methods to detect human behaviour changes is the use of supervised techniques that require human intervention. This work proposes an automatic data mining method based on physical activity measurements. Abnormal human behaviour is detected as an increase or decrease of the physical activity according to the historical data. Human behaviour is evaluated in real time grading its abnormality. The method has been validated involving users with a precision of 100% and a recall of 92%. © 2014 Elsevier B.V. All rights reserved. Source


Carus J.L.,Fundacion CTIC Centro Tecnologico | Pelaez V.,Fundacion CTIC Centro Tecnologico | Lopez G.,Fundacion CTIC Centro Tecnologico | Lobato V.,Fundacion CTIC Centro Tecnologico
Studies in Health Technology and Informatics | Year: 2012

There are various techniques available to measure human physical activity (PA). Accelerometer based techniques claim to be non-invasive and easy to use. The signal magnitude area (SMA) is the most extended feature used to measure the physical activity. It is calculated by sampling and filtering an accelerometer signal of at least at 50 Hz. SMA has a proven and widely accepted linear relation with the energy expenditure. A novel magnitude called JIM, which is more efficient than SMA, is proposed in this paper. The jerk-based inactivity magnitude (JIM) is also calculated from the acceleration signal, but at a sampling rate of 1Hz, increasing the battery life of the measuring system. This magnitude gives the same information as the SMA (correlation of 95%) and is validated with a group of 39 users in free-living conditions for at least 24 hours. © 2012 The authors and IOS Press. All rights reserved. Source

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