Un outil d’évaluation neurocognitive des interactions humain-machine

De plus en plus de recherches sur les Interactions Humain-Machine (IHM) tentent d’effectuer des analyses fines de l’interaction afin de faire ressortir ce qui influence les comportements des utilisateurs. Tant au niveau de l’évaluation de la performance que de l’expérience des utilisateurs, on note qu’une attention particulière est maintenant portée aux réactions émotionnelles et cognitives lors de l’interaction. Les approches qualitatives standards sont limitées, car elles se fondent sur l’observation et des entrevues après l’interaction, limitant ainsi la précision du diagnostic. L’expérience utilisateur et les réactions émotionnelles étant de nature hautement dynamique et contextualisée, les approches d’évaluation doivent l’être de même afin de permettre un diagnostic précis de l’interaction. Cette thèse présente une approche d’évaluation quantitative et dynamique qui permet de contextualiser les réactions des utilisateurs afin d’en identifier les antécédents dans l’interaction avec un système. Pour ce faire, ce travail s’articule autour de trois axes. 1) La reconnaissance automatique des buts et de la structure de tâches de l’utilisateur, à l’aide de mesures oculométriques et d’activité dans l’environnement par apprentissage machine. 2) L’inférence de construits psychologiques (activation, valence émotionnelle et charge cognitive) via l’analyse des signaux physiologiques. 3) Le diagnostic de l‘interaction reposant sur le couplage dynamique des deux précédentes opérations. Les idées et le développement de notre approche sont illustrés par leur application dans deux contextes expérimentaux : le commerce électronique et l’apprentissage par simulation. Nous présentons aussi l’outil informatique complet qui a été implémenté afin de permettre à des professionnels en évaluation (ex. : ergonomes, concepteurs de jeux, formateurs) d’utiliser l’approche proposée pour l’évaluation d’IHM. Celui-ci est conçu de manière à faciliter la triangulation des appareils de mesure impliqués dans ce travail et à s’intégrer aux méthodes classiques d’évaluation de l’interaction (ex. : questionnaires et codage des observations).More and more researches on Human-Computer Interactions (HCI) are trying to perform detailed analyses of interaction to determine its influence on users’ behaviours. A particular emphasis is now put on emotional reactions during the interaction, whether it’s from the perspective of user experience evaluation or user performance. Standard qualitative approaches are limited because they are based on observations and interviews after the interaction, therefore limiting the precision of the diagnosis. User experience and emotional reactions being, by nature, highly dynamic and contextualized, evaluation approaches should be the same to accurately diagnose the quality of interaction. This thesis presents an evaluation approach, both dynamic and quantitative, which allows contextualising users’ emotional reactions to help identify their causes during the interaction with a system. To this end, our work focuses on three main axes: 1) automatic task recognition using machine learning modeling of eye tracking and interaction data; 2) automatic inference of psychological constructs (emotional activation, emotional valence, and cognitive load) through physiological signals analysis; and 3) diagnosis of users’ reactions during interaction based on the coupling of the two previous operations. The ideas and development of our approach are illustrated using two experimental contexts: e-commerce and simulation-based training. We also present the tool we implemented in order to allow HCI professionals (e.g.: user experience expert, training supervisor, or game designer) to use our evaluation approach to assess interaction. This tool is designed to facilitate the triangulation of measuring instruments and the integration with more classical Human-Computer Interaction methods (ex.: surveys and observation coding)

Emotional Maps for User Experience Research in the Wild

While most traditional user experience (UX) evaluation methods (e.g., questionnaires) have made the transition to the “wild”, physiological measurements still strongly rely upon controlled lab settings. As part of an ongoing research agenda, this paper presents a novel approach for UX research which contributes to this transition. The proposed method triangulates GPS and physiological data to create emotional maps, which outline geographical areas where users experienced specific emotional states in outdoor environments. The method is implemented as a small portable recording device, and a data visualization software. A field study was conducted in an amusement park to test the proposed approach. Emotional maps highlighting the areas where users experienced varying levels of arousal are presented. We also discuss insights uncovered, and how UX practitioners could use the approach to bring their own research into the wild

Precision is in the Eye of the Beholder: Application of Eye Fixation-Related Potentials to Information Systems Research

This paper introduces the eye-fixation related potential (EFRP) method to IS research. The EFRP method allows one to synchronize eye tracking with electroencephalographic (EEG) recording to precisely capture users’ neural activity at the exact time at which they start to cognitively process a stimulus (e.g., event on the screen). This complements and overcomes some of the shortcomings of the traditional event related potential (ERP) method, which can only stamp the time at which a stimulus is presented to a user. Thus, we propose a method conjecture of the superiority of EFRP over ERP for capturing the cognitive processing of a stimulus when such cognitive processing is not necessarily synchronized with the time at which the stimulus appears. We illustrate the EFRP method with an experiment in a natural IS use context in which we asked users to read an industry report while email pop-up notifications arrived on their screen. The results support our proposed hypotheses and show three distinct neural processes associated with 1) the attentional reaction to email pop-up notification, 2) the cognitive processing of the email pop-up notification, and 3) the motor planning activity involved in opening or not the email. Furthermore, further analyses of the data gathered in the experiment serve to validate our method conjecture about the superiority of the EFRP method over the ERP in natural IS use contexts. In addition to the experiment, our study discusses important IS research questions that could be pursued with the aid of EFRP, and describes a set of guidelines to help IS researchers use this method

Dynamic Threshold Selection for a Biocybernetic Loop in an Adaptive Video Game Context

Passive Brain-Computer interfaces (pBCIs) are a human-computer communication tool where the computer can detect from neurophysiological signals the current mental or emotional state of the user. The system can then adjust itself to guide the user toward a desired state. One challenge facing developers of pBCIs is that the system's parameters are generally set at the onset of the interaction and remain stable throughout, not adapting to potential changes over time such as fatigue. The goal of this paper is to investigate the improvement of pBCIs with settings adjusted according to the information provided by a second neurophysiological signal. With the use of a second signal, making the system a hybrid pBCI, those parameters can be continuously adjusted with dynamic thresholding to respond to variations such as fatigue or learning. In this experiment, we hypothesize that the adaptive system with dynamic thresholding will improve perceived game experience and objective game performance compared to two other conditions: an adaptive system with single primary signal biocybernetic loop and a control non-adaptive game. A within-subject experiment was conducted with 16 participants using three versions of the game Tetris. Each participant plays 15 min of Tetris under three experimental conditions. The control condition is the traditional game of Tetris with a progressive increase in speed. The second condition is a cognitive load only biocybernetic loop with the parameters presented in Ewing et al. (2016). The third condition is our proposed biocybernetic loop using dynamic threshold selection. Electroencephalography was used as the primary signal and automatic facial expression analysis as the secondary signal. Our results show that, contrary to our expectations, the adaptive systems did not improve the participants' experience as participants had more negative affect from the BCI conditions than in the control condition. We endeavored to develop a system that improved upon the authentic version of the Tetris game, however, our proposed adaptive system neither improved players' perceived experience, nor their objective performance. Nevertheless, this experience can inform developers of hybrid passive BCIs on a novel way to employ various neurophysiological features simultaneously

Évaluation de la charge cognitive lors de l'apprentissage pour un support tutoriel approprié

Ce mémoire aborde deux thèmes faisant partie du domaine des systèmes tutoriels intelligents. Un modèle de l'apprenant reposant sur des théories psychologiques de l'apprentissage et du traitement de l'information sera d'abord présenté, suivi de deux stratégies pédagogiques tirant profit de ce modèle. L'objectif général du projet de recherche est d'enrichir, à l'aide d'un modèle cognitif, l'information disponible pour un système tutoriel dans le but de promouvoir plus efficacement l'acquisition de connaissances lors d'activités d'apprentissage. Un laboratoire de soustractions en base hexadécimale a été développé dans le but de tester et de valider l'approche proposée. Un article ayant fait l'objet d'une publication et détaillant une partie du projet de recherche est présenté dans chacun des trois chapitres de ce mémoire

Évaluation de la charge cognitive lors de l'apprentissage pour un support tutoriel approprié

Ce mémoire aborde deux thèmes faisant partie du domaine des systèmes tutoriels intelligents. Un modèle de l'apprenant reposant sur des théories psychologiques de l'apprentissage et du traitement de l'information sera d'abord présenté, suivi de deux stratégies pédagogiques tirant profit de ce modèle. L'objectif général du projet de recherche est d'enrichir, à l'aide d'un modèle cognitif, l'information disponible pour un système tutoriel dans le but de promouvoir plus efficacement l'acquisition de connaissances lors d'activités d'apprentissage. Un laboratoire de soustractions en base hexadécimale a été développé dans le but de tester et de valider l'approche proposée. Un article ayant fait l'objet d'une publication et détaillant une partie du projet de recherche est présenté dans chacun des trois chapitres de ce mémoire

The Double Drum Peel (DDP) test: a new concept to evaluate the delamination fracture toughness of cylindrical laminates

International audienceStandard delamination tests of monolithic composites prescribe configurations where the crack is a symmetry plane for both overall geometry and stacking sequence, ensuring a controlled mode ratio. These normalized configurations do not enable testing of curved specimens, like those manufactured by filament winding. Here, we propose a new concept for the delamination testing of cylindrical laminates, the Double Drum Peel, related to the peel tests used for adhesives or thin-films debonding. A global energy analysis, including all sources of energy release and dissipation, provides the expression of the critical strain energy release rate. As in the classical peel test, the energy dissipated by mechanisms other than delamination should be accounted for to determine intrinsic interface properties. The local mode mixity is evaluated based on analytical results on the classical peel test. Tests using carbon-peek rings manufactured by laser assisted tape placement are presented to illustrate the potential of the DDP

Deepkøver an adaptive intelligent assistance system for monitoring impaired people in smart homes

International audienceThe chapter presents a novel modular adaptive artful intelligent assistance system for cognitively and/or memory impaired people engaged in the realisation of their activities of daily living (ADLs). The goal of this assistance system is to help disabled persons moving/evolving within a controlled environment in order to provide logistic support in achieving their ADLs. Empirical results of practical tests are presented and interpreted. Some deductions about the key features that represent originalities of the assistance system are drawn and future works are announce