Languages for safety-certification related propertis

The Safety Certification of Software-Intensive Systems with Reusable Components project, in short SafeCer (www.safecer.eu),is targeting increased efficiency and reduced time-to-market by composable safety certification of safety- relevant embedded systems. The industrial domains targeted are within automotive and construction equipment, avionics, and rail. Some of the companies involved are: Volvo Tech- nology, Thales, TTTech, and Intecs among others. SafeCer includes more than 30 partners in six different countries and has a budget of e25.7 millions. A primary objective is to provide support for system safety arguments based on arguments and properties of system components as well as to provide support for generation of corresponding evidence in a similar compositional way. By providing support for efficient reuse of certification and stronger links between certification and development, compo- nent reuse will be facilitated, and by providing support for reuse across domains the amount of components available for reuse will increase dramatically. The resulting efficiency and reduced time to market will, together with increased quality and reduced risk, increase competitiveness and pave the way for a cross-domain market for software components qualified for certification.

Performance assessment of an architecture with adaptative interfaces for people with special needs

People in industrial societies carry more and more portable electronic devices (e.g., smartphone or console) with some kind of wireles connectivity support. Interaction with auto-discovered target devices present in the environment (e.g., the air conditioning of a hotel) is not so easy since devices may provide inaccessible user interfaces (e.g., in a foreign language that the user cannot understand). Scalability for multiple concurrent users and response times are still problems in this domain. In this paper, we assess an interoperable architecture, which enables interaction between people with some kind of special need and their environment. The assessment, based on performance patterns and antipatterns, tries to detect performance issues and also tries to enhance the architecture design for improving system performance. As a result of the assessment, the initial design changed substantially. We refactorized the design according to the Fast Path pattern and The Ramp antipattern. Moreover, resources were correctly allocated. Finally, the required response time was fulfilled in all system scenarios. For a specific scenario, response time was reduced from 60 seconds to less than 6 seconds.

How Continuous Monitoring Changes the Interaction of Patients with a Mobile Telemedicine System

The use of continuous glucose monitor changes the way patients manage their diabetes, as observed in the increased number of daily insulin bolus, the increased number of daily BG measurements, and the differences in the distribution of BG measurements throughout the day. Continuous monitoring also increases the interaction of patients with the information system and modifies their patterns of use.

eCONSULTA: Integración de un Sistema de Videoconsultoría Web entre Asistencia Primaria y Atención Especializada

En este artículo presentamos un sistema de videoconferencia web de bajo coste cuyo objetivo es mejorar la comunicación entre Atención Primaria y Atención Especializada optimizando los recursos y la calidad de la atención en enfermedades con alta prevalencia en la actualidad. En este caso se utiliza para problemas metabólicos como la diabetes o patologías del tiroides, aunque podría ser aplicado a otras patologías. El sistema está basado en una herramienta de SW libre (OpenMeetings) adaptada a nuestras necesidades y a la que se han añadido funcionalidades importantes como una sala de espera virtual o la administración de agendas. eCONSULTA ha sido instalado en el Servicio de Endocrinología y Nutrición del Hospital de Sabadell e integrado en el sistema de información médico de los Centros de Atención Primaria de la comarca del Vallés Occidental, provincia de Barcelona. En el momento de la redacción del artículo se está realizando un estudio de viabilidad y satisfacción de los usuarios.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

TRHIOS: Trust and reputation in hierarchical and quality-oriented societies

In this paper we present TRHIOS: a Trust and Reputation system for HIerarchical and quality-Oriented Societies. We focus our work on hierarchical medical organizations. The model estimates the reputation of an individual, RTRHIOS, taking into account information from three trust dimensions: the hierarchy of the system; the source of information; and the quality of the results. Besides the concrete reputation value, it is important to know how reliable that value is; for each of the three dimensions we calculate the reliability of the assessed reputations; and aggregating them, the reliability of the reputation of an individual. The modular approach followed in the definition of the different types of reputations provides the system with a high flexibility that allows adapting the model to the peculiarities of each society.

Integración de dispositivos de salud personal en la plataforma de telecuidado para diabetes PERSONA

La plataforma de telecuidado PERSONA se ha desarrollado en el marco del CIBER-BBN y tiene por objetivo soportar el autocuidado diario de pacientes con diabetes tipo 1. La plataforma proporciona acceso a herramientas de soporte a la decisión, de procesado automático de la información, de monitorización de las variables que afectan a la enfermedad y facilita la comunicación entre los agentes involucrados en el cuidado del paciente. La integración de dispositivos médicos interoperables es un requisito principal de la plataforma PERSONA. En este trabajo presentamos las soluciones adoptadas en cuanto a la integración de dispositivos médicos y analizamos las características de los protocolos de comunicación inalámbrica de los dispositivos considerados y los recursos necesarios para la comunicación con dispositivos móviles de telefonía.

Aplicación de la especificación Data Distribution Service (DDS) al control de glucosa en pacientes diabéticos

En este trabajo se ha investigado la posibilidad de utilizar el estándar DDS (Data Distribution Service) desarrollado por el OMG (Object Management Group) para la monitorización en tiempo real del nivel de glucosa en pacientes diabéticos. Dicho estándar sigue el patrón publicador/suscriptor de modo que, en la prueba de concepto desarrollada, los sensores del punto de cuidado son publicadores de los valores de glucosa de los pacientes y diferentes supervisores se suscriben a esa información. Estos supervisores reaccionan de la forma más adecuada a los valores y la evolución del nivel de glucosa en el paciente, por ejemplo, registrando el valor de la muestra o generando una alarma. El software de intermediación que soporta la comunicación de datos sigue el estándar DDS. Esto facilita por un lado la escalabilidad e interoperatividad de la solución desarrollada y por otro la monitorización de niveles de glucosa y la activación de protocolos predefinidos en tiempo real. La investigación se enmarca dentro del proyecto intramural PERSONA del CIBER-BBN, cuyo objetivo es el diseño de herramientas de soporte a la decisión para la monitorización continua de pacientes personalizadas e integradas en una plataforma tecnológica para diabetes.

PREDIRCAM eHealth platform for individualized telemedical assistance for lifestyle modification in the treatment of obesity, diabetes, and cardiometabolic risk prevention: a pilot study (PREDIRCAM 1)

Background: Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic risk prevention. Methods: PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness of lifestyle behavior modifications through the intensive use of the latest information and communication technologies. The platform consists of a web-based application providing communication interface with monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic medical records, different communication channels, and an intelligent notification system. A 2-week feasibility study was conducted in 15 volunteers to assess the viability of the platform. Results: The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded (average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of the volunteers considered long-term use of the platform to be feasible. Conclusions: The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform and, in particular, for registration of dietary food intake.

Patient-oriented computerized clinical guidelines for mobile decision support in gestational diabetes

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient’s access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients’ personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients’ acceptance of the whole system.

Design evaluation of a prototype user interface to support a guideline-based decision support system in gestational diabetes

Gestational Diabetes (GD) has increased over the last 20 years, affecting up to 15% of pregnant women worldwide. The complications associated can be reduced with the appropriate glycemic control during the pregnancy.

Tour virtual: una forma eficiente de realizar evaluaciones tempranas en aplicaciones de paciente

Tradicionalmente, los sistemas de ayuda a la decisión (Decision Support Systems, DSS) han estado dirigidos a los profesionales médicos; sin embargo también pueden ayudar a aquellos pacientes que desean tener un papel más activo en el cuidado de su salud. Además, los pacientes quieren ser tratados en el momento en que su estado de salud lo requiera, sin importar el lugar en el que se encuentren. El sistema MobiGuide proporciona un soporte personalizado y basado en evidencia clínica tanto a profesionales médicos como a pacientes en todo momento y en todo lugar. La aplicación móvil del paciente representa el punto de acceso al servicio y, por tanto, es responsable en gran medida del éxito o fracaso del sistema. En MobiGuide, se ha incorporado a los pacientes desde el comienzo en el proceso de diseño y evaluación de la aplicación para garantizar una adecuada funcionalidad y usabilidad del sistema. En este trabajo presentamos la primera evaluación realizada por los pacientes mediante un tour virtual por la Aplicación de Paciente. Los resultados son altamente positivos y útiles para mejorar la aplicación, corregir defectos y conseguir la aplicación final esperada por los pacientes.

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

El auge y penetración de las nuevas tecnologías junto con la llamada Web Social están cambiando la forma en la que accedemos a la medicina. Cada vez más pacientes y profesionales de la medicina están creando y consumiendo recursos digitales de contenido clínico a través de Internet, surgiendo el problema de cómo asegurar la fiabilidad de estos recursos. Además, un nuevo concepto está apareciendo, el de pervasive healthcare o sanidad ubicua, motivado por pacientes que demandan un acceso a los servicios sanitarios en todo momento y en todo lugar. Este nuevo escenario lleva aparejado un problema de confianza en los proveedores de servicios sanitarios. Las plataformas de eLearning se están erigiendo como paradigma de esta nueva Medicina 2.0 ya que proveen un servicio abierto a la vez que controlado/supervisado a recursos digitales, y facilitan las interacciones y consultas entre usuarios, suponiendo una buena aproximación para esta sanidad ubicua. En estos entornos los problemas de fiabilidad y confianza pueden ser solventados mediante la implementación de mecanismos de recomendación de recursos y personas de manera confiable. Tradicionalmente las plataformas de eLearning ya cuentan con mecanismos de recomendación, si bien están más enfocados a la recomendación de recursos. Para la recomendación de usuarios es necesario acudir a mecanismos más elaborados como son los sistemas de confianza y reputación (trust and reputation) En ambos casos, tanto la recomendación de recursos como el cálculo de la reputación de los usuarios se realiza teniendo en cuenta criterios principalmente subjetivos como son las opiniones de los usuarios. En esta tesis doctoral proponemos un nuevo modelo de confianza y reputación que combina evaluaciones automáticas de los recursos digitales en una plataforma de eLearning, con las opiniones vertidas por los usuarios como resultado de las interacciones con otros usuarios o después de consumir un recurso. El enfoque seguido presenta la novedad de la combinación de una parte objetiva con otra subjetiva, persiguiendo mitigar el efecto de posibles castigos subjetivos por parte de usuarios malintencionados, a la vez que enriquecer las evaluaciones objetivas con información adicional acerca de la capacidad pedagógica del recurso o de la persona. El resultado son recomendaciones siempre adaptadas a los requisitos de los usuarios, y de la máxima calidad tanto técnica como educativa. Esta nueva aproximación requiere una nueva herramienta para su validación in-silico, al no existir ninguna aplicación que permita la simulación de plataformas de eLearning con mecanismos de recomendación de recursos y personas, donde además los recursos sean evaluados objetivamente. Este trabajo de investigación propone pues una nueva herramienta, basada en el paradigma de programación orientada a agentes inteligentes para el modelado de comportamientos complejos de usuarios en plataformas de eLearning. Además, la herramienta permite también la simulación del funcionamiento de este tipo de entornos dedicados al intercambio de conocimiento. La evaluación del trabajo propuesto en este documento de tesis se ha realizado de manera iterativa a lo largo de diferentes escenarios en los que se ha situado al sistema frente a una amplia gama de comportamientos de usuarios. Se ha comparado el rendimiento del modelo de confianza y reputación propuesto frente a dos modos de recomendación tradicionales: a) utilizando sólo las opiniones subjetivas de los usuarios para el cálculo de la reputación y por extensión la recomendación; y b) teniendo en cuenta sólo la calidad objetiva del recurso sin hacer ningún cálculo de reputación. Los resultados obtenidos nos permiten afirmar que el modelo desarrollado mejora la recomendación ofrecida por las aproximaciones tradicionales, mostrando una mayor flexibilidad y capacidad de adaptación a diferentes situaciones. Además, el modelo propuesto es capaz de asegurar la recomendación de nuevos usuarios entrando al sistema frente a la nula recomendación para estos usuarios presentada por el modo de recomendación predominante en otras plataformas que basan la recomendación sólo en las opiniones de otros usuarios. Por último, el paradigma de agentes inteligentes ha probado su valía a la hora de modelar plataformas virtuales complejas orientadas al intercambio de conocimiento, especialmente a la hora de modelar y simular el comportamiento de los usuarios de estos entornos. La herramienta de simulación desarrollada ha permitido la evaluación del modelo de confianza y reputación propuesto en esta tesis en una amplia gama de situaciones diferentes. ABSTRACT Internet is changing everything, and this revolution is especially present in traditionally offline spaces such as medicine. In recent years health consumers and health service providers are actively creating and consuming Web contents stimulated by the emergence of the Social Web. Reliability stands out as the main concern when accessing the overwhelming amount of information available online. Along with this new way of accessing the medicine, new concepts like ubiquitous or pervasive healthcare are appearing. Trustworthiness assessment is gaining relevance: open health provisioning systems require mechanisms that help evaluating individuals’ reputation in pursuit of introducing safety to these open and dynamic environments. Technical Enhanced Learning (TEL) -commonly known as eLearning- platforms arise as a paradigm of this Medicine 2.0. They provide an open while controlled/supervised access to resources generated and shared by users, enhancing what it is being called informal learning. TEL systems also facilitate direct interactions amongst users for consultation, resulting in a good approach to ubiquitous healthcare. The aforementioned reliability and trustworthiness problems can be faced by the implementation of mechanisms for the trusted recommendation of both resources and healthcare services providers. Traditionally, eLearning platforms already integrate recommendation mechanisms, although this recommendations are basically focused on providing an ordered classifications of resources. For users’ recommendation, the implementation of trust and reputation systems appears as the best solution. Nevertheless, both approaches base the recommendation on the information from the subjective opinions of other users of the platform regarding the resources or the users. In this PhD work a novel approach is presented for the recommendation of both resources and users within open environments focused on knowledge exchange, as it is the case of TEL systems for ubiquitous healthcare. The proposed solution adds the objective evaluation of the resources to the traditional subjective personal opinions to estimate the reputation of the resources and of the users of the system. This combined measure, along with the reliability of that calculation, is used to provide trusted recommendations. The integration of opinions and evaluations, subjective and objective, allows the model to defend itself against misbehaviours. Furthermore, it also allows ‘colouring’ cold evaluation values by providing additional quality information such as the educational capacities of a digital resource in an eLearning system. As a result, the recommendations are always adapted to user requirements, and of the maximum technical and educational quality. To our knowledge, the combination of objective assessments and subjective opinions to provide recommendation has not been considered before in the literature. Therefore, for the evaluation of the trust and reputation model defined in this PhD thesis, a new simulation tool will be developed following the agent-oriented programming paradigm. The multi-agent approach allows an easy modelling of independent and proactive behaviours for the simulation of users of the system, conforming a faithful resemblance of real users of TEL platforms. For the evaluation of the proposed work, an iterative approach have been followed, testing the performance of the trust and reputation model while providing recommendation in a varied range of scenarios. A comparison with two traditional recommendation mechanisms was performed: a) using only users’ past opinions about a resource and/or other users; and b) not using any reputation assessment and providing the recommendation considering directly the objective quality of the resources. The results show that the developed model improves traditional approaches at providing recommendations in Technology Enhanced Learning (TEL) platforms, presenting a higher adaptability to different situations, whereas traditional approaches only have good results under favourable conditions. Furthermore the promotion period mechanism implemented successfully helps new users in the system to be recommended for direct interactions as well as the resources created by them. On the contrary OnlyOpinions fails completely and new users are never recommended, while traditional approaches only work partially. Finally, the agent-oriented programming (AOP) paradigm has proven its validity at modelling users’ behaviours in TEL platforms. Intelligent software agents’ characteristics matched the main requirements of the simulation tool. The proactivity, sociability and adaptability of the developed agents allowed reproducing real users’ actions and attitudes through the diverse situations defined in the evaluation framework. The result were independent users, accessing to different resources and communicating amongst them to fulfil their needs, basing these interactions on the recommendations provided by the reputation engine.