Inner-Hair Cells Parameterized-Hardware Implementation for Personalized Auditory Nerve Stimulation

In this paper the hardware implementation of an inner hair cell model is presented. Main features of the design are the use of Meddis’ transduction structure and the methodology for Design with Reusability. Which allows future migration to new hardware and design refinements for speech processing and custom-made hearing aids

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

On the localization of the personalized PageRank of complex networks

In this paper new results on personalized PageRank are shown. We consider directed graphs that may contain dangling nodes. The main result presented gives an analytical characterization of all the possible values of the personalized PageRank for any node.We use this result to give a theoretical justification of a recent model that uses the personalized PageRank to classify users of Social Networks Sites. We introduce new concepts concerning competitivity and leadership in complex networks. We also present some theoretical techniques to locate leaders and competitors which are valid for any personalization vector and by using only information related to the adjacency matrix of the graph and the distribution of its dangling nodes.

Personalized rule-based closed-loop control algorithm for type 1 diabetes

Type 1 diabetes-mellitus implies a life-threatening absolute insulin deficiency. Artificial pancreas (CGM sensor, insulin pump and control algorithm) is promising to outperform current open-loop therapies.

Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.

Standards and specifications to manage accessibility issues in e-learning

Despite the acknowledged need of providing a personalized and adaptive learning process for all, current learning management systems do not properly cover personalization and accessibility issues and they are still struggling to support the reusability requirements coming from the pervasive usage of standards. There is a lack of frameworks for providing layered-based infrastructure covering the interoperability required to manage the whole range of standards, applications and services needed to meet accessibility and adaptations needs of lifelong learning services.

A low power routing algorithm for localization in IEEE 802.15.4 networks

Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

Opportunities in the Mobile Search Market

Success in the mobile search market will come to those who provide value-added apps that exploit unique mobile functionalities, especially those related to personalized and context-based services.

Innovative self management system for guided cardiac rehabilitation

This paper describes the design and development of a system for cardio rehabilitation of patients that suffered a myocardial infarction. The proposed solution focuses on exercise prescriptions and the encouragement of healthy behaviors. The innovative strategy of the design takes into account health promotion models to provide safe, assistive exercise training sessions, personalized feedbacks, and educational contents.

Metodologías de modelado, monitorización y asistencia robótica en neurorrehabilitación funcional de extremidad superior

La Organización Mundial de la Salud (OMS) prevé que para el año 2020, el Daño Cerebral Adquirido (DCA) estará entre las 10 causas más comunes de discapacidad. Estas lesiones, dadas sus consecuencias físicas, sensoriales, cognitivas, emocionales y socioeconómicas, cambian dramáticamente la vida de los pacientes y sus familias. Las nuevas técnicas de intervención precoz y el desarrollo de la medicina intensiva en la atención al DCA han mejorado notablemente la probabilidad de supervivencia. Sin embargo, hoy por hoy, las lesiones cerebrales no tienen ningún tratamiento quirúrgico que tenga por objetivo restablecer la funcionalidad perdida, sino que las terapias rehabilitadoras se dirigen hacia la compensación de los déficits producidos. Uno de los objetivos principales de la neurorrehabilitación es, por tanto, dotar al paciente de la capacidad necesaria para ejecutar las Actividades de Vida Diaria (AVDs) necesarias para desarrollar una vida independiente, siendo fundamentales aquellas en las que la Extremidad Superior (ES) está directamente implicada, dada su gran importancia a la hora de la manipulación de objetos. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma centrado en ofrecer una práctica personalizada, monitorizada y ubicua con una valoración continua de la eficacia y de la eficiencia de los procedimientos y con capacidad de generar conocimientos que impulsen la ruptura del paradigma de actual. Los nuevos objetivos consistirán en minimizar el impacto de las enfermedades que afectan a la capacidad funcional de las personas, disminuir el tiempo de incapacidad y permitir una gestión más eficiente de los recursos. Estos objetivos clínicos, de gran impacto socio-económico, sólo pueden alcanzarse desde una apuesta decidida en nuevas tecnologías, metodologías y algoritmos capaces de ocasionar la ruptura tecnológica necesaria que permita superar las barreras que hasta el momento han impedido la penetración tecnológica en el campo de la rehabilitación de manera universal. De esta forma, los trabajos y resultados alcanzados en la Tesis son los siguientes: 1. Modelado de AVDs: como paso previo a la incorporación de ayudas tecnológicas al proceso rehabilitador, se hace necesaria una primera fase de modelado y formalización del conocimiento asociado a la ejecución de las actividades que se realizan como parte de la terapia. En particular, las tareas más complejas y a su vez con mayor repercusión terapéutica son las AVDs, cuya formalización permitirá disponer de modelos de movimiento sanos que actuarán de referencia para futuros desarrollos tecnológicos dirigidos a personas con DCA. Siguiendo una metodología basada en diagramas de estados UML se han modelado las AVDs 'servir agua de una jarra' y 'coger un botella' 2. Monitorización ubícua del movimiento de la ES: se ha diseñado, desarrollado y validado un sistema de adquisición de movimiento basado en tecnología inercial que mejora las limitaciones de los dispositivos comerciales actuales (coste muy elevado e incapacidad para trabajar en entornos no controlados); los altos coeficientes de correlación y los bajos niveles de error obtenidos en los corregistros llevados a cabo con el sistema comercial BTS SMART-D demuestran la alta precisión del sistema. También se ha realizado un trabajo de investigación exploratorio de un sistema de captura de movimiento de coste muy reducido basado en visión estereoscópica, habiéndose detectado los puntos clave donde se hace necesario incidir desde un punto de vista tecnológico para su incorporación en un entorno real 3. Resolución del Problema Cinemático Inverso (PCI): se ha diseñado, desarrollado y validado una solución al PCI cuando el manipulador se corresponde con una ES humana estudiándose 2 posibles alternativas, una basada en la utilización de un Perceptrón Multicapa (PMC) y otra basada en sistemas Artificial Neuro-Fuzzy Inference Systems (ANFIS). La validación, llevada a cabo utilizando información relativa a los modelos disponibles de AVDs, indica que una solución basada en un PMC con 3 neuronas en la capa de entrada, una capa oculta también de 3 neuronas y una capa de salida con tantas neuronas como Grados de Libertad (GdLs) tenga el modelo de la ES, proporciona resultados, tanto de precisión como de tiempo de cálculo, que la hacen idónea para trabajar en sistemas con requisitos de tiempo real 4. Control inteligente assisted-as-needed: se ha diseñado, desarrollado y validado un algoritmo de control assisted-as-needed para una ortesis robótica con capacidades de actuación anticipatoria de la que existe un prototipo implementado en la actualidad. Los resultados obtenidos demuestran cómo el sistema es capaz de adaptarse al perfil disfuncional del paciente activando la ayuda en instantes anteriores a la ocurrencia de movimientos incorrectos. Esta estrategia implica un aumento en la participación del paciente y, por tanto, en su actividad muscular, fomentándose los procesos la plasticidad cerebral responsables del reaprendizaje o readaptación motora 5. Simuladores robóticos para planificación: se propone la utilización de un simulador robótico assisted-as-needed como herramienta de planificación de sesiones de rehabilitación personalizadas y con un objetivo clínico marcado en las que interviene una ortesis robotizada. Los resultados obtenidos evidencian como, tras la ejecución de ciertos algoritmos sencillos, es posible seleccionar automáticamente una configuración para el algoritmo de control assisted-as-needed que consigue que la ortesis se adapte a los criterios establecidos desde un punto de vista clínico en función del paciente estudiado. Estos resultados invitan a profundizar en el desarrollo de algoritmos más avanzados de selección de parámetros a partir de baterías de simulaciones Estos trabajos han servido para corroborar las hipótesis de investigación planteadas al inicio de la misma, permitiendo, asimismo, la apertura de nuevas líneas de investigación. Summary The World Health Organization (WHO) predicts that by the year 2020, Acquired Brain Injury (ABI) will be among the ten most common ailments. These injuries dramatically change the life of the patients and their families due to their physical, sensory, cognitive, emotional and socio-economic consequences. New techniques of early intervention and the development of intensive ABI care have noticeably improved the survival rate. However, in spite of these advances, brain injuries still have no surgical or pharmacological treatment to re-establish the lost functions. Neurorehabilitation therapies address this problem by restoring, minimizing or compensating the functional alterations in a person disabled because of a nervous system injury. One of the main objectives of Neurorehabilitation is to provide patients with the capacity to perform specific Activities of the Daily Life (ADL) required for an independent life, especially those in which the Upper Limb (UL) is directly involved due to its great importance in manipulating objects within the patients' environment. The incorporation of new technological aids to the neurorehabilitation process tries to reach a new paradigm focused on offering a personalized, monitored and ubiquitous practise with continuous assessment of both the efficacy and the efficiency of the procedures and with the capacity of generating new knowledge. New targets will be to minimize the impact of the sicknesses affecting the functional capabilitiies of the subjects, to decrease the time of the physical handicap and to allow a more efficient resources handling. These targets, of a great socio-economic impact, can only be achieved by means of new technologies and algorithms able to provoke the technological break needed to beat the barriers that are stopping the universal penetration of the technology in the field of rehabilitation. In this way, this PhD Thesis has achieved the following results: 1. ADL Modeling: as a previous step to the incorporation of technological aids to the neurorehabilitation process, it is necessary a first modelling and formalization phase of the knowledge associated to the execution of the activities that are performed as a part of the therapy. In particular, the most complex and therapeutically relevant tasks are the ADLs, whose formalization will produce healthy motion models to be used as a reference for future technological developments. Following a methodology based on UML state-chart diagrams, the ADLs 'serving water from a jar' and 'picking up a bottle' have been modelled 2. Ubiquitous monitoring of the UL movement: it has been designed, developed and validated a motion acquisition system based on inertial technology that improves the limitations of the current devices (high monetary cost and inability of working within uncontrolled environments); the high correlation coefficients and the low error levels obtained throughout several co-registration sessions with the commercial sys- tem BTS SMART-D show the high precision of the system. Besides an exploration of a very low cost stereoscopic vision-based motion capture system has been carried out and the key points where it is necessary to insist from a technological point of view have been detected 3. Inverse Kinematics (IK) problem solving: a solution to the IK problem has been proposed for a manipulator that corresponds to a human UL. This solution has been faced by means of two different alternatives, one based on a Mulilayer Perceptron (MLP) and another based on Artificial Neuro-Fuzzy Inference Systems (ANFIS). The validation of these solutions, carried out using the information regarding the previously generated motion models, indicate that a MLP-based solution, with an architecture consisting in 3 neurons in the input layer, one hidden layer of 3 neurons and an output layer with as many neurons as the number of Degrees of Freedom (DoFs) that the UL model has, is the one that provides the best results both in terms of precission and in terms of processing time, making in idoneous to be integrated within a system with real time restrictions 4. Assisted-as-needed intelligent control: an assisted-as-needed control algorithm with anticipatory actuation capabilities has been designed, developed and validated for a robotic orthosis of which there is an already implemented prototype. Obtained results demonstrate that the control system is able to adapt to the dysfunctional profile of the patient by triggering the assistance right before an incorrect movement is going to take place. This strategy implies an increase in the participation of the patients and in his or her muscle activity, encouraging the neural plasticity processes in charge of the motor learning 5. Planification with a robotic simulator: in this work a robotic simulator is proposed as a planification tool for personalized rehabilitation sessions under a certain clinical criterium. Obtained results indicate that, after the execution of simple parameter selection algorithms, it is possible to automatically choose a specific configuration that makes the assisted-as-needed control algorithm to adapt both to the clinical criteria and to the patient. These results invite researchers to work in the development of more complex parameter selection algorithms departing from simulation batteries Obtained results have been useful to corroborate the hypotheses set out at the beginning of this PhD Thesis. Besides, they have allowed the creation of new research lines in all the studied application fields.

Modelado de sistemas multimedia para personalización y recomendación híbrida a partir del consumo audiovisual de los usuarios

This doctoral thesis focuses on the modeling of multimedia systems to create personalized recommendation services based on the analysis of users’ audiovisual consumption. Research is focused on the characterization of both users’ audiovisual consumption and content, specifically images and video. This double characterization converges into a hybrid recommendation algorithm, adapted to different application scenarios covering different specificities and constraints. Hybrid recommendation systems use both content and user information as input data, applying the knowledge from the analysis of these data as the initial step to feed the algorithms in order to generate personalized recommendations. Regarding the user information, this doctoral thesis focuses on the analysis of audiovisual consumption to infer implicitly acquired preferences. The inference process is based on a new probabilistic model proposed in the text. This model takes into account qualitative and quantitative consumption factors on the one hand, and external factors such as zapping factor or company factor on the other. As for content information, this research focuses on the modeling of descriptors and aesthetic characteristics, which influence the user and are thus useful for the recommendation system. Similarly, the automatic extraction of these descriptors from the audiovisual piece without excessive computational cost has been considered a priority, in order to ensure applicability to different real scenarios. Finally, a new content-based recommendation algorithm has been created from the previously acquired information, i.e. user preferences and content descriptors. This algorithm has been hybridized with a collaborative filtering algorithm obtained from the current state of the art, so as to compare the efficiency of this hybrid recommender with the individual techniques of recommendation (different hybridization techniques of the state of the art have been studied for suitability). The content-based recommendation focuses on the influence of the aesthetic characteristics on the users. The heterogeneity of the possible users of these kinds of systems calls for the use of different criteria and attributes to create effective recommendations. Therefore, the proposed algorithm is adaptable to different perceptions producing a dynamic representation of preferences to obtain personalized recommendations for each user of the system. The hypotheses of this doctoral thesis have been validated by conducting a set of tests with real users, or by querying a database containing user preferences - available to the scientific community. This thesis is structured based on the different research and validation methodologies of the techniques involved. In the three central chapters the state of the art is studied and the developed algorithms and models are validated via self-designed tests. It should be noted that some of these tests are incremental and confirm the validation of previously discussed techniques. Resumen Esta tesis doctoral se centra en el modelado de sistemas multimedia para la creación de servicios personalizados de recomendación a partir del análisis de la actividad de consumo audiovisual de los usuarios. La investigación se focaliza en la caracterización tanto del consumo audiovisual del usuario como de la naturaleza de los contenidos, concretamente imágenes y vídeos. Esta doble caracterización de usuarios y contenidos confluye en un algoritmo de recomendación híbrido que se adapta a distintos escenarios de aplicación, cada uno de ellos con distintas peculiaridades y restricciones. Todo sistema de recomendación híbrido toma como datos de partida tanto información del usuario como del contenido, y utiliza este conocimiento como entrada para algoritmos que permiten generar recomendaciones personalizadas. Por la parte de la información del usuario, la tesis se centra en el análisis del consumo audiovisual para inferir preferencias que, por lo tanto, se adquieren de manera implícita. Para ello, se ha propuesto un nuevo modelo probabilístico que tiene en cuenta factores de consumo tanto cuantitativos como cualitativos, así como otros factores de contorno, como el factor de zapping o el factor de compañía, que condicionan la incertidumbre de la inferencia. En cuanto a la información del contenido, la investigación se ha centrado en la definición de descriptores de carácter estético y morfológico que resultan influyentes en el usuario y que, por lo tanto, son útiles para la recomendación. Del mismo modo, se ha considerado una prioridad que estos descriptores se puedan extraer automáticamente de un contenido sin exigir grandes requisitos computacionales y, de tal forma que se garantice la posibilidad de aplicación a escenarios reales de diverso tipo. Por último, explotando la información de preferencias del usuario y de descripción de los contenidos ya obtenida, se ha creado un nuevo algoritmo de recomendación basado en contenido. Este algoritmo se cruza con un algoritmo de filtrado colaborativo de referencia en el estado del arte, de tal manera que se compara la eficiencia de este recomendador híbrido (donde se ha investigado la idoneidad de las diferentes técnicas de hibridación del estado del arte) con cada una de las técnicas individuales de recomendación. El algoritmo de recomendación basado en contenido que se ha creado se centra en las posibilidades de la influencia de factores estéticos en los usuarios, teniendo en cuenta que la heterogeneidad del conjunto de usuarios provoca que los criterios y atributos que condicionan las preferencias de cada individuo sean diferentes. Por lo tanto, el algoritmo se adapta a las diferentes percepciones y articula una metodología dinámica de representación de las preferencias que permite obtener recomendaciones personalizadas, únicas para cada usuario del sistema. Todas las hipótesis de la tesis han sido debidamente validadas mediante la realización de pruebas con usuarios reales o con bases de datos de preferencias de usuarios que están a disposición de la comunidad científica. La diferente metodología de investigación y validación de cada una de las técnicas abordadas condiciona la estructura de la tesis, de tal manera que los tres capítulos centrales se estructuran sobre su propio estudio del estado del arte y los algoritmos y modelos desarrollados se validan mediante pruebas autónomas, sin impedir que, en algún caso, las pruebas sean incrementales y ratifiquen la validación de técnicas expuestas anteriormente.

Novel system for bite-force sensing and monitoring based on magnetic eear field communication

Intraoral devices for bite-force sensing have several applications in odontology and maxillofacial surgery, as bite-force measurements provide additional information to help understand the characteristics of bruxism disorders and can also be of help for the evaluation of post-surgical evolution and for comparison of alternative treatments. A new system for measuring human bite forces is proposed in this work. This system has future applications for the monitoring of bruxism events and as a complement for its conventional diagnosis. Bruxism is a pathology consisting of grinding or tight clenching of the upper and lower teeth, which leads to several problems such as lesions to the teeth, headaches, orofacial pain and important disorders of the temporomandibular joint. The prototype uses a magnetic field communication scheme similar to low-frequency radio frequency identification (RFID) technology (NFC). The reader generates a low-frequency magnetic field that is used as the information carrier and powers the sensor. The system is notable because it uses an intra-mouth passive sensor and an external interrogator, which remotely records and processes information regarding a patient?s dental activity. This permits a quantitative assessment of bite-force, without requiring intra-mouth batteries, and can provide supplementary information to polysomnographic recordings, current most adequate early diagnostic method, so as to initiate corrective actions before irreversible dental wear appears. In addition to describing the system?s operational principles and the manufacture of personalized prototypes, this report will also demonstrate the feasibility of the system and results from the first in vitro and in vivo trials.

BioMet®Tools: from modeling and simulation to product design and development

BioMet®Tools is a set of software applications developed for the biometrical characterization of voice in different fields as voice quality evaluation in laryngology, speech therapy and rehabilitation, education of the singing voice, forensic voice analysis in court, emotional detection in voice, secure access to facilities and services, etc. Initially it was conceived as plain research code to estimate the glottal source from voice and obtain the biomechanical parameters of the vocal folds from the spectral density of the estimate. This code grew to what is now the Glottex®Engine package (G®E). Further demands from users in medical and forensic fields instantiated the development of different Graphic User Interfaces (GUI’s) to encapsulate user interaction with the G®E. This required the personalized design of different GUI’s handling the same G®E. In this way development costs and time could be saved. The development model is described in detail leading to commercial production and distribution. Study cases from its application to the field of laryngology and speech therapy are given and discussed.

Virtual Excursions: a new way to explore science in class

The educational platform Virtual Science Hub (ViSH) has been developed as part of the GLOBAL excursion European project. ViSH (http://vishub.org/) is a portal where teachers and scientist interact to create virtual excursions to science infrastructures. The main motivation behind the project was to connect teachers - and in consequence their students - to scientific institutions and their wide amount of infrastructures and resources they are working with. Thus the idea of a hub was born that would allow the two worlds of scientists and teachers to connect and to innovate science teaching. The core of the ViSH?s concept design is based on virtual excursions, which allow for a number of pedagogical models to be applied. According to our internal definition a virtual excursion is a tour through some digital context by teachers and pupils on a given topic that is attractive and has an educational purpose. Inquiry-based learning, project-based and problem-based learning are the most prominent approaches that a virtual excursion may serve. The domain specific resources and scientific infrastructures currently available on the ViSH are focusing on life sciences, nano-technology, biotechnology, grid and volunteer computing. The virtual excursion approach allows an easy combination of these resources into interdisciplinary teaching scenarios. In addition, social networking features support the users in collaborating and communicating in relation to these excursions and thus create a community of interest for innovative science teaching. The design and development phases were performed following a participatory design approach. An important aspect in this process was to create design partnerships amongst all actors involved, researchers, developers, infrastructure providers, teachers, social scientists, and pedagogical experts early in the project. A joint sense of ownership was created and important changes during the conceptual phase were implemented in the ViSH due to early user feedback. Technology-wise the ViSH is based on the latest web technologies in order to make it cross-platform compatible so that it works on several operative systems such as Windows, Mac or Linux and multi-device accessible, such as desktop, tablet and mobile devices. The platform has been developed in HTML5, the latest standard for web development, assuring that it can run on any modern browser. In addition to social networking features a core element on the ViSH is the virtual excursions editor. It is a web tool that allows teachers and scientists to create rich mash-ups of learning resources provided by the e-Infrastructures (i.e. remote laboratories and live webcams). These rich mash-ups can be presented in either slides or flashcards format. Taking advantage of the web architecture supported, additional powerful components have been integrated like a recommendation engine to provide personalized suggestions about educational content or interesting users and a videoconference tool to enhance real-time collaboration like MashMeTV (http://www.mashme.tv/).