Towards the Quality Improvement of Web Applications by Neuroscience Techniques

User-centered design not only requires designers to analyse and anticipate how users are likely to use a Web application, but also to validate their assumptions with regard to user behaviour in real environments. Cognitive neuroscience, for its part, addresses the questions of how psychological functions are produced by neural circuitry. The emergence of powerful new measurement techniques allows neuroscientists and psychologists to address abstract questions such as how human cognition and emotion are mapped to specific neural substrates. This paper focus on the validation of user-centered designs and requirements of Web applications by neuroscience techniques and suggest the use of these techniques to achieve efficient and effectiveness validated designs by real behavior of potential users.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-RJunta de Andalucía TIC-578

Identités Numériques : apports des interfaces nomades aux seniors

International audienc

Pedestrian crossing decision-making: A situational and behavioral approach

Among road users, pedestrians are those whose continued trajectory is the less constrained by the environment and by the regulation rules. Consequently, the choice of where, when and how to cross roads are more or less conforming with the awaited behavior. Proceeding with an experimental approach, from observations of pedestrian crossings to the modeling of the decision-making process, a categorization of both environments and of pedestrian behavior is proposed

Modeling users' search through contextual graphs.

National audienceThis paper presents a work on a comparison between a user model and user's behavior based on three premises. First, any system includes a representation of its users. Second, the external representation of users in a system is related to how the system is used by users. Third, knowing how to use the system depends on the task context. For making context explicit in order to use it, we use contextual graphs to capture the effective behaviors of users in an activity of information retrieval on a scientific website. We show how such a context-based representation may help to predict the search behavior of visitors to the website pages. We extend the capability of the system by a preliminary study based on a technique of eye tracking coupled with the contextual-graph representation. This approach allows dealing with a system that is able to incrementally acquire new knowledge from the user and learn new practices when the system is in a situation of failure.Ce papier présente un travail sur la comparaison entre un modèle utilisateur et le comportement réel de l'utilisateur reposant sur trois prémisses : 1) tout système interagissant avec un utilisateur possède un modèle de celui-ci ; 2) la représentation externe des utilisateurs dépend de l'utilisation qui est faite du système par l'utilisateur ; 3) connaître le type d'utilisation du système dépend du contexte dans lequel la tâche doit être exécutée. L'explicitation du contexte en vue de son utilisation conduit à utiliser les graphes contextuels pour capturer les comportements effectifs des utilisateurs dans une activité de recherche d'information sur un site web scientifique. Nous avons étendu les capacités d'un système d'aide dans une étude préliminaire basée sur une technique de repérage de mouvements oculaires en couplage avec la représentation en graphes contextuels. Cette approche permet de composer avec un système capable d'acquérir de manière incrémentale de nouvelles connaissances de l'utilisateur, et ainsi apprendre de nouvelles pratiques développées par les utilisateurs quand il est en échec

Analogy and metaphors in images

International audienc

Human Heuristics for a Team of Mobile Robots

Abstract — This paper is at the crossroad of Cognitive Psychology and AI Robotics. It reports a cross-disciplinary project concerned about implementing human heuristics within autonomous mobile robots. In the following, we address the problem of relying on human-based heuristics to endow a group of mobile robots with the ability to solve problems such as target finding in a labyrinth. Such heuristics may provide an efficient way to explore the environment and to decompose a complex problem into subtasks for which specific heuristics are efficient. We first present a set of experiments conducted with group of humans looking for a target with limited sensing capabilities solving. Then we describe the heuristics extracted from the observation and analysis of their behavior. Finally we implemented these heuristics within khepera-like autonomous mobile robots facing the same tasks. We show that the control architecture can be experimentally validated to some extent thanks to this approach. I

Evaluation of sensory properties using hierarchical scales of verbal items

National audienc

Evaluation of sensory properties using hierarchical scales of verbal items

National audienc