10 research outputs found
InCense IoT: A Collective Sensing System for Behavior Data in Shared Spaces
Behavioral sensing systems collect data from smartphones, wearables, and other devices
with the aim of analyzing and making sense of them. In this work, we present InCense IoT, a
collective sensing system which uses mobile and ubiquitous sensors for collecting behavior data of
groups of participants in shared spaces. This paper describes the concept of collective sensing, an
implementation onto InCense called InCense IoT, innovative features, advantages over
individual-centric sensing systems. Finally, this paper presents results of a use case using it in
monitoring behaviors in mother-child interactions
A Hybrid Model Using Hidden Markov Chain and Logic Model for Daily Living Activity Recognition
We detail the solution to the UCAmI Cup Challenge to recognizing on going activities at home from sensor measurements. We use binary sensors and proximity sensor measurements for the recognition. We use an hybrid strategy, combining a probabilistic model and a definition-based model. The former consists of a Hidden Markov Model using the result of a neural network as emission probabilities. It is trained with the labelled data provided by the Cup. The latter approach takes advantage of the descriptions provided for each of the activities which are expressed in logical statements based on the sensors states. We then combine the results with a weighted average. We compare the performance of each individual strategy and of the combined strategy.12th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2018), 4–7 December 2018, Punta Cana, Dominican Republi
Discovering user's trends and routines from location based social networks
ABSTRACT: Location data is a powerful source of information to discover user's trends and routines. A suitable identification of the user context can be exploited to provide automatically services adapted to the user preferences. In this paper, we define a Dynamic Bayesian Network model and propose a method that processes location annotated data in order to train the model. Finally, our model enables us to predict future location contexts from the user patterns. A case study evaluates the proposal using real-world data of a location-based social network.This research was funded by Fondo Europeo de Desarrollo Regional (FEDER) and Sociedad para el
Desarrollo Regional de Cantabria (SODERCAN) grant number TI16-IN-007 (within the program “I+C=+C 2016-
PROYECTOS DE I+D EN EL ÁMBITO DE LAS TIC, LÍNEA SMART”), and by Ministerio de Ciencia e Innovación
(MICINN), Spain grant number MTM2014-55262-P (project PAC::LFO)
Intelligent Monitoring of Affective Factors Underlying Sport Performance by Means of Wearable and Mobile Technology
The fluctuation of affective states is a contributing factor to sport performance variability.
The context surrounding athletes during their daily life and the evolution of their physiological
variables beyond sport events are relevant factors, as they modulate the affective state of the
subject over time. However, traditional procedures to assess the affective state are limited to
self-reported questionnaires within controlled settings, thus removing the impact of the context.
This work proposes a multimodal, context-aware platform that combines the data acquired through
smartphones and wearable sensors to assess the affective state of the athlete. The platform is aimed
at ubiquitously monitoring the fluctuations of affective states during longitudinal studies within
naturalistic environments, overcoming the limitations of previous studies and allowing for the
complete evaluation of the factors that could modulate the affective state. This system will also
facilitate and expedite the analysis of the relationship between affective states and sport performance.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness
(MINECO) Projects TIN2015-71873-R and TIN2015-67020-P together with the European Fund for Regional
Development (FEDER). This work has also been partially supported by the FPU Spanish Grant FPU16/04376 and
the Dutch UT-CTIT project HoliBehave
Ubiquitous Assessment of the Recovery of Cancer Patients Using Consumer-Level Activity Trackers
Performance Status (PS) variability is a powerful tool to evaluate overall condition,
treatment needs and survival chances of cancer patients. Traditionally, its assessment has relied on the
experience of oncologists when interpreting results of clinical tests and when interviewing the patients.
Meanwhile, consumer-level activity trackers have obtained good results in behavior-change oriented
intervention trials and Fitbit devices have demonstrated enough reliability to provide objective data
related to physical activity, but the clinical possibilities of the data collected has been neglected.
This work presents a system design for ubiquitous assessment of PS by means of objective and
quantifiable data from different sources: medical history, self-reported quality-of-life questionnaires
and a commercial activity tracker Fitbit Alta HR. The system proposed aims to contextualize and
model the recovery process of breast cancer patients during chemotherapy treatment.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness
(MINECO) Projects TIN2015-71873-R and TIN2015-67020-P together with the European Fund for Regional
Development (FEDER). This work has also been partially supported by the FPU Spanish Grant FPU16/04201
Architecture for Efficient String Dictionaries in E-Learning
E-Learning is a response to the new educational needs of society and an important development in Information and Communication Technologies. However, this trend presents many challenges, such as the lack of an architecture that allows a unified management of heterogeneous string dictionaries required by all the users of e-learning environments, which we face in this paper. We mean the string dictionaries needed in information retrieval, content development, “key performance indicators” generation and course management applications. As an example, our approach can deal with different indexation dictionaries required by the course contents and the different online forums that generate a huge number of messages with an unordered structure and a great variety of topics. Our architecture will generate an only dictionary that is shared by all the stakeholders involved in the e-learning process.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) under Project SEQUOIA-UA (TIN2015-63502-C3-3-R), Project RESCATA (TIN2015-65100-R) and Project PROMETEO/2018/089; and in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under Project CloudDriver4Industry (TIN2017-89266-R)
Application of the BPM Strategy to the Management of the COPD Clinical Process
Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death according to the World Health Organization (WHO). Like any chronic disease, the clinical process of COPD affects the patient’s life. Currently, clinical processes are inefficient, causing a loss of quality of life for patients and a high economic increase in the costs borne by family members, health systems and society. This paper presents a new approach to the redesign of the process for the management of COPD based on the use of the strategy of continuous improvement Business Process Management. This approach aims to improve the efficiency of the management of chronic diseases such as COPD, while achieving a higher quality of life and patient satisfaction.This work has been granted by the Ministerio de Economía y Competitividad of the Spanish Government (ref. TIN2014-53067-C3-1-R and ref. BES-2015-073611)
A Study on the Perceptions of Autistic Adolescents towards Mainstream Emotion Recognition Technologies
Autistic people have difficulties in recognizing and expressing emotions from/to other
people. Technologies can help to facilitate the communication and understanding between autistic
and other people. This work particularly investigates the requirements autistic adolescents have on
technologies that can measure bodily responses to recognize their emotions. A smartwatch, smartpatch
and infrared camera were evaluated as potential everyday use devices to measure emotion.
User requirements on emotion recognition technologies were elicited through an online survey (73
completed responses) and ten semi-structured interviews with autistic adolescents. The smartwatch
is the preferred product, followed by the smart-patch. Infrared cameras are deemed unsuitable
devices.This research was partly funded by the research project “Progress in Computer Architectures for
Automatic Learning using Heterogeneous Sources: Health and Well-Being Applications” (TIN2015-71873-R)
Technology Support for Collaborative Preparation of Emergency Plans
Indexación: Scopus.Preparing a plan for reaction to a grave emergency is a significant first stage in disaster management. A group of experts can do such preparation. Best results are obtained with group members having diverse backgrounds and access to different relevant data. The output of this stage should be a plan as comprehensive as possible, taking into account various perspectives. The group can organize itself as a collaborative decision-making team with a process cycle involving modeling the process, defining the objectives of the decision outcome, gathering data, generating options and evaluating them according to the defined objectives. The meeting participants may have their own evidences concerning people’s location at the beginning of the emergency and assumptions about people’s reactions once it occurs. Geographical information is typically crucial for the plan, because the plan must be based on the location of the safe areas, the distances to move people, the connecting roads or other evacuation links, the ease of movement of the rescue personnel, and other geography-based considerations. The paper deals with this scenario and it introduces a computer tool intended to support the experts to prepare the plan by incorporating the various viewpoints and data. The group participants should be able to generate, visualize and compare the outcomes of their contributions. The proposal is complemented with an example of use: it is a real case simulation in the event of a tsunami following an earthquake at a certain urban location. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.https://www.mdpi.com/1424-8220/19/22/504
Nuevas metodologías para el reconocimiento de cambios posturales a través de sensores
Con el fin de posibilitar nuevas alternativas que permitan mitigar la complicación de las úlceras por presión, en este trabajo se presentan los resultados de investigación de la tesis doctoral, que han permitido implementar dos metodologías de reconocimiento de cambios posturales de monitoreo en tiempo real, con dispositivos vestibles inerciales no invasivos para la detección y cálculo de postura, usando técnicas de inteligencia artificial. La primera metodología está basada en un registro histórico de la actividad corporal, dataset, y por el reconocimiento de posturas en tiempo real con técnicas de Inteligencia Artificial. Por su parte, la segunda metodología comprende el uso de dispositivos vestibles inerciales en zonas no invasivas, encargados de registrar el tiempo en que la persona ha permanecido en la misma posición, la recolección de datos de personas reales en diferentes posturas, la estimación de las posturas en tiempo real se realiza mediante técnicas de inteligencia artificial.To enable new alternatives to mitigate the complication of pressure ulcers, this work presents the research results of the doctoral thesis, which have allowed the implementation of two real-time monitoring methodologies, with devices non-invasive inertial wearables for posture detection and calculation and using artificial intelligence techniques. The first methodology is based on a historical record of body activity, a dataset, and the recognition of postures in real-time with Artificial Intelligence techniques. On other hand, the second methodology includes the use of inertial wearable devices in non-invasive areas, recording the time the person has remained in the same position, the collection of data from real people in key ulcer prevention positions, the estimation of postures in real-time using artificial intelligence techniques.Tesis Univ. Jaén. Departamento de Informática. Leída el 19/11/2021