In this work, the benefits of Ambient Intelligence for enhancing user experience with Brain Computer Interfaces are explored. In a smart-home environment, statistics of devices activations are used to learn user habits and to adapt the interface for providing the most usual option to the user, reducing the time spent navigating through hierarchical menus. The activation statistics are learned by discriminative machine learning algorithms able to provide the most suitable options for the user interface. Promising experimental results on simulated scenarios encourage following on this research direction.

SUMMARY: Spatial data visualization is very useful to represent biological data and quickly interpret the results. For instance, to show the expression pattern of a gene in different tissues of a fly, an intuitive approach is to draw the fly with the corresponding tissues and color the expression of the gene in each of them. However, the creation of these visual representations may be a burdensome task. Here we present SVGMap, a java application that automatizes the generation of high-quality graphics for singular data items (e.g. genes) and biological conditions. SVGMap contains a browser that allows the user to navigate the different images created and can be used as a web-based results publishing tool. AVAILABILITY: SVGMap is freely available as precompiled java package as well as source code at http://bg.upf.edu/svgmap. It requires Java 6 and any recent web browser with JavaScript enabled. The software can be run on Linux, Mac OS X and Windows systems. CONTACT: [email protected]

This paper focuses on the problem of representing, in a meaningful way, the knowledge involved in the HealthAgents project. Our work is motivated by the complexity of representing electronic healthcare records in a consistent manner. We present HADOM (HealthAgents domain ontology) which conceptualises the required HealthAgents information and propose describing the sources knowledge by the means of conceptual graphs (CGs). This allows to build upon the existing ontology permitting for modularity and flexibility. The novelty of our approach lies in the ease with which CGs can be placed above other formalisms and their potential for optimised querying and retrieval.