Système intelligent pour le suivi et l’optimisation de l’état cognitif

Les émotions des êtres humains changent régulièrement et parfois de manière brusque entrainant un changement de l’état mental c’est-à-dire de l’aptitude cérébrale à fonctionner normalement. Il en résulte une capacité cognitive (ou état cognitif) de l’individu à pouvoir raisonner, accéder à la mémoire, ou effectuer des déductions, variable selon l’état mental. Ceci affecte, en conséquence, les performances des utilisateurs qui varient en fonction de leurs état cognitifs. Cette thèse vise à optimiser l’état cognitif d’un utilisateur lors de ses interactions avec un environnement virtuel. Comme cet état dépend des émotions, l’optimisation de l’état cognitif peut être réalisée à travers l’optimisation des émotions et en particulier la réduction des émotions négatives. Une première partie concerne les moyens de mesurer en temps réel (par un Module de mesures) l’état émotionnel et mental d’un utilisateur lors de ses interactions avec un environnement virtuel. Nous avons réalisé pour cela quatre études expérimentales avec quatre environnements différents. Nous avons montré que ces mesures peuvent être réalisées en utilisant différents capteurs physiologiques. Nous avons aussi montré qu’il est possible de prédire la tendance de l’excitation (un état mental) à partir d’un traceur de regard. Dans une deuxième partie, nous présentons l’Agent Neural qui modifie les environnements virtuels afin de provoquer une modification de l’état émotionnel d’un utilisateur pour améliorer son état cognitif. Nous avons réalisé quatre études expérimentales avec quatre environnements virtuels, où l’Agent Neural intervient dans ces environnements afin de changer l’état émotionnel de l’utilisateur. Nous avons montré que l’agent est capable d’intervenir dans plusieurs types d’environnements et de modifier les émotions de l’utilisateur. Dans une troisième partie, présentons l’Agent Limbique, qui personnalise et améliore les adaptations faites par l’Agent Neural à travers l’observation et l’apprentissage des impacts des changements des environnements virtuels et des réactions émotionnelles des utilisateurs. Nous avons montré que cet agent est capable d’analyser les interventions de l’Agent Neural et de les modifier. Nous avons montré aussi que l’Agent Limbique est capable de générer une nouvelle règle d’intervention et de prédire son impact sur l’utilisateur. La combinaison du Module de mesures, de l’Agent Neural, et de l’Agent Limbique, nous a permis de créer un système de contrôle cognitif intelligent que nous avons appelé Système Limbique Digital.The human’s emotions change regularly and sometimes suddenly leading to changes in their mental state which is the brain’s ability to function normally. This mental state’s changes affect the users’ cognitive ability (or cognitive state) to reason, access memory, or make inferences, which varies depending on the mental state. Consequently, this affects the users’ performances which varies according to their cognitive states. This thesis aims to optimize the users’ cognitive state during their interactions with a virtual environment. Since this state depends on emotions, optimization of cognitive state can be achieved through the optimization of emotions and in particular the reduction of negative emotions. In a first part, we present the means of measuring in real time (using a Measuring module) the users’ emotional and mental state during their interactions with a virtual environment. We performed four experimental studies with four different environments. We have shown that these measurements can be performed using different physiological sensors. We have also shown that it is possible to predict the tendency of excitement (a mental state) using an eye tracker. In a second part, we present the Neural Agent which modifies virtual environments to provoke a modification on the users’ emotional state in order to improve their cognitive state. We performed four experimental studies with four virtual environments, in which the Neural Agent intervenes in these environments to change the users’ emotional state. We have shown that the agent is able to intervene in several types of environments and able to modify the users’ emotions. In a third part, we present the Limbic Agent, which personalizes and improves the adaptations performed by the Neural Agent through the observation and the learning from the virtual environments changes’ impacts and the users’ emotional reactions. We have shown that this agent is able to analyze the Neural Agent’s interventions and able to modify them. We have also shown that the Limbic Agent is able to generate a new intervention rule and predict its impact on the user. The combination of the Measuring Module, the Neural Agent, and the Limbic Agent, allowed us to create an intelligent cognitive control system that we called the Digital Limbic System

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Study, definition and analysis of pilot/system performance measurements for planetary entry experiments

Definition analysis for experimental prediction of pilot performance during planetary entr

Investigation of possible causes for human-performance degradation during microgravity flight

The results of the first year of a three year study of the effects of microgravity on human performance are given. Test results show support for the hypothesis that the effects of microgravity can be studied indirectly on Earth by measuring performance in an altered gravitational field. The hypothesis was that an altered gravitational field could disrupt performance on previously automated behaviors if gravity was a critical part of the stimulus complex controlling those behaviors. In addition, it was proposed that performance on secondary cognitive tasks would also degrade, especially if the subject was provided feedback about degradation on the previously automated task. In the initial experimental test of these hypotheses, there was little statistical support. However, when subjects were categorized as high or low in automated behavior, results for the former group supported the hypotheses. The predicted interaction between body orientation and level of workload in their joint effect on performance in the secondary cognitive task was significant for the group high in automatized behavior and receiving feedback, but no such interventions were found for the group high in automatized behavior but not receiving feedback, or the group low in automatized behavior

Developing augmented reality capabilities for industry 4.0 small enterprises: Lessons learnt from a content authoring case study

Augmented reality (AR) has been proposed as a disruptive and enabling technology within the Industry 4.0 manufacturing paradigm. The complexity of the AR content creation process results in an inability for Small Enterprise (SE)to create bespoke,flexibleARtraining support “in-house” and is a potential barrier to industrial adoption of AR. Presently, AR content creation requires a range of specialist knowledge (e.g. 3D modelling, interface design, programming and spatial tracking) and may involve infrastructure changes (e.g. fiducial markers, cameras) and disruption to workflow. The research reported in this paper concerns the development and deployment of an Augmented Repair Training Application (ARTA); a templatebased interface to support end user (shop floor) AR content creation. The proposed methodology and implementation are discussed and evaluated in a real-world industrial case study in collaboration with a Small Enterprise (SE) in the Used and Waste Electronic and Electrical Equipment sector (UEEE/WEEE). The need for end user friendly templates is presented in the conclusion alongside further related work

Using body sensors for evaluating the impact of smart cycling technologies on cycling experiences:a systematic literature review and conceptual framework

Digital technologies in, on, and around bicycles and cyclists are gaining ground. Collectively called Smart Cycling Technologies (SCTs), it is important to evaluate their impact on subjective cycling experiences. Future evaluations can inform the design of SCTs, which in turn can help to realize the abundant benefits of cycling. Wearable body sensors and advanced driver assistance systems are increasingly studied in other domains, however evaluation methods integrating such sensors and systems in the field of cycling research were under-reviewed and under-conceptualized. This paper therefore presents a systematic literature review and conceptual framework to support the use of body sensors in evaluations of the impact of SCTs on perceptions, emotions, feelings, affect, and more, during outdoor bicycle rides. The literature review (n = 40) showed that there is scarce research on this specific use of body sensors. Moreover, existing research designs are typically not tailored to determine impact of SCTs on cycling experience at large scale. Most studies had small sample sizes and explored limited sensors in chest belts and wristbands for evaluating stress response. The evaluation framework helps to overcome these limitations, by synthesizing crucial factors and methods for future evaluations in four categories: (1) experiences with SCTs, (2) experience measurements, (3) causal analysis, (4) confounding variables. The framework also identifies which types of sensors fit well to which types of experiences and SCTs. The seven directions for future research include, for example, experiences of psychological flow, sensors in e-textiles, and cycling with biofeedback. Future interactions between cyclists and SCTs will likely resemble a collaboration between humans and artificial intelligence. Altogether, this paper helps to understand if future support systems for cyclists truly make cycling safer and more attractive