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International audience; This work explores how the design and situatedness of data representations affect people’s compassion with a case study concerning harassment episodes in a public place. Results contribute to advancing the understanding of how visualizations can evoke emotions and their impact on prosocial behaviors, such as helping people in need. Recent literature examined the effect of different on-screen data representations on emotion or prosociality, but little has been done concerning visualizations shown in a public place — especially a space contextually relevant to the data — or presented through unconventional media formats such as physical marks. We conducted two in-the-wild studies to investigate how different factors affect people’s self-reported compassion and intention to donate. We compared three ways of presenting data about the harassment cases: (1) communicating data only verbally; (2) using a printed poster with aggregated information; and (3) using a physicalization with detailed information about each story. We found that the physicalization influenced people to donate more than only hearing about the data, but it is unclear if the same applied to the poster visualization. Also, passers-by reported a likely small increase in compassion when they saw the physicalization instead of the poster. We also examined the role of situatedness by showing the physicalization in a site that is not contextually relevant to the data. Our results suggest that people had a similar intention to donate and levels of compassion in both places. Those findings may indicate that using specific visualization designs to support campaigns about sensitive causes (e.g., sexual harassment) can increase the emotional response of passers-by and may motivate them to help, independently of where the data representation is shown. Finally, this work also informs on the strengths and weaknesses of using research in the wild to evaluate data visualizations in public spaces.

The negative impact humans have on the environment is partly caused by thoughtless consumption leading to unnecessary waste. A likely contributing factor is the relative invisibility of waste: waste produced by individuals is either out of their sight or quickly taken away. Nevertheless, waste disposal systems sometimes break down, creating natural information displays of waste production that can have educational value. We take inspiration from such natural displays and introduce a class of situated visualizations we call augmented-reality waste accumulation visualizations or ARwavs, which are literal representations of waste data embedded in users' familiar environment. We implemented examples of ARwavs and demonstrated them in feedback sessions with experts in pro-environmental behavior, and during a large tech exhibition event. We discuss general design principles and trade-offs for ARwavs. Finally, we conducted a study suggesting that ARwavs yield stronger emotional responses than non-immersive waste accumulation visualizations and plain numbers.

Best student paper award ICRAT 2020; International audience; Moving object analysis is a constantly growing field with numerous concrete applications in terms of traffic understanding, prediction and simulation. While many algorithms and analytic processes exist, there are still areas of investigation with novel trajectory analysis methods. As such, the geometric information analyses data with respect to its statistical distribution along extracted dimensions. This opens new ways of gaining a better understanding of large and complex trajectory data sets while providing flexible data manipulations. In this paper, we report our investigations with the development of an interactive methodology based on the geometric information analytic process where users can analyze trajectories sets, cluster and deform them maintaining the actual statistical properties of the investigated trajectories. As a contribution, this paper shows how geometric information can provide novel support for trajectory analyses taking into account the statistical properties of the investigated clusters. We also provide recommendations of good usage of such techniques with actual examples validated by a a domain expert of air traffic flow analysis

International audience; This paper presents a novel approach for phone-level pronunciation scoring. The proposed method relies on the two usual stages of pronunciation scoring: an acoustic model transcribes the spoken utterance into a phoneme sequence and then, Weighted-Dynamic Time Warping (W-DTW) is used to compare the predicted phoneme sequence against the reference one. Our approach alters the comparison process by considering Phonetic PosteriorGrams (PPG) rather than only the most probable sequence of phonemes. This led us to pro- pose a modified W-DTW algorithm that considers the probabilities of the predicted phonemes, as well as the use of articulatory features as a proxy of phonetic similarity. The results achieved are satisfactory considering the content of the adult speech database and are comparable to well-known state-of- the-art methods.

Cet article présente des expériences d’application de la réalité virtuelle et de la réalité augmentée dans des cas d’usage issus du spectacle vivant. Nous décrivons les échanges avec les professionnels de quatre institutions du spectacle vivant : l’Opéra de Paris, le théâtre du Monfort, le Conservatoire National Supérieur de Musique et de Danse de Paris, et l’académie Fratellini. Ces échanges ont donné lieu à l’expression de besoins dont nous proposons une classification, et à une série de projets ayant tous abouti à la conception d’applications interactives 3D temps réel, de formats variés, AR, VR, smartphone, desktop, par les élèves ingénieurs. Nous discutons de la rencontre entre artistes et ingénieurs, et exposons les conclusions informelles sur l’intérêt des approches XR pour le spectacle vivant.

International audience; Over recent years, we witnessed an astonishing growth in production and consumption of Linked Data (LD), which contains valuable information to support decision-making processes in various application domains. In this context, data visualization plays a decisive role in making sense of the large volumes of data created every day and in effectively communicating structures, processes, and trends in data in an accessible way. In this paper, we present LDViz, a visualization tool designed to support the exploration of knowledge graphs via multiple perspectives: (i) RDF graph/vocabulary inspection, (ii) RDF summarization, and (iii) exploratory search. We demonstrate the usage and feasibility of our approach through a set of use case scenarios showing how users can perform searches through SPARQL queries and explore multiple perspectives of the resulting data through multiple complementary visualization techniques. We also demonstrate the reach and generic aspects of our tool through an evaluation that tests the support of 419 different SPARQL endpoints.

International audience; L’étude et la modélisation des interactions entre piétons et usagers de fauteuil roulant électrique (FRE) est un enjeu majeur pour le développement d’assistance à la conduite de tels fauteuils, notamment pour suivre l’intention de déplacement de l’usager tout en évitant une collision avec un piéton à proximité. Pour mieux comprendre les intentions et les distances de proximité piéton-FRE lors de déplacement en groupe, nous avons demandé à un usager de FRE de rejoindre un groupe de deux piétons, marchant côte à côte. Les marcheurs se déplaçaient d’un point de départ à un point d’arrivée situé en face à 20m. Le participant en FRE arrivait perpendiculairement à la trajectoire des marcheurs. Ils devaient alors tous les trois rejoindre ensemble le point d’arrivée. 9 participants marchant (8 hommes, 1 femme, 27ans) et 3 usagers de FRE (3 hommes, 43 ans) ont participé à cette étude. 2 des usagers de FRE étaient ergothérapeutes, 1 avaient une paralysie cérébrale. Trois sessions incluant 1 usager de FRE et 3 marcheurs ont été réalisées. Chaque paire de marcheurs a réalisé 10 essais, pour un total de 20 essais par marcheur et 30 essais pour l’usager en FRE. L’analyse en cours porte sur les adaptations de mouvement de la personne en FRE et des piétons ainsi que leurs positions relatives. Il s’agit alors d’étudier le comportement d’interaction qui permet aux marcheurs et à l’usager de FRE de former un groupe, les distances de proximité ainsi que de potentielles asymétries marcheur-marcheur et marcheur usager de FRE.

International audience; In order to motivate the user to change her/his behavior or attitudes, for instance to practice physical activities to improve her/his well-being, virtual agents should have persuasive capabilities. The persuasiveness of the virtual agent not only depends on its speech but also on its non-verbal behavioral cues. In this paper, we propose the new tool called THRUST (from neuTral Human face to peRsUaSive virTual face), to automatically generate the head movements and facial expressions of a persuasive virtual character from a video of a human. Combining a machine learning approach on a corpus of persuasive human speech and a convolution-based method, we propose a model, based on real data of persuasive human message, that transforms the non-verbal behavior of the human expressed in a video to a persuasive non-verbal behavior replicated on a virtual face.

International audience; While immersive media have been shown to generate more intense emotions, saliency information has been shown to be a key component for the assessment of their quality, owing to the various portions of the sphere (viewports) a user can attend. In this article, we investigate the tri-partite connection between user attention, user emotion and visual content in immersive environments. To do so, we present a new dataset enabling the analysis of different types of saliency, both lowlevel and high-level, in connection with the user's state in 360 • videos. Head and gaze movements are recorded along with self-reports and continuous physiological measurements of emotions. We then study how the accuracy of saliency estimators in predicting user attention depends on user-reported and physiologically-sensed emotional perceptions. Our results show that high-level saliency better predicts user attention for higher levels of arousal. We discuss how this work serves as a first step to understand and predict user attention and intents in immersive interactive environments.

International audience; Due to abundant signal and user variability among others, BCIs remain difficult to control. To increase performance, adaptive methods are a necessary means to deal with such a vast spectrum of variable data. Typically, adaptive methods deal with the signal or classification corrections (adaptive spatial filters [1], co-adaptive calibration [2], adaptive classifiers [3]). As such, they do not necessarily account for the implicit alterations they perform on the feedback (in real-time), and in turn, on the user, creating yet another potential source of unpredictable variability. Namely, certain user's personality traits and states have shown to correlate with BCI performance, while feedback can impact user states [4]. For instance, altered (biased) feedback was distorting the participants' perception over their performance, influencing their feeling of control, and online performance [5]. Thus, one can assume that through feedback we might implicitly guide the user towards a desired state beneficial for BCI performance. We propose a novel, simple probabilistic, data-driven dynamic model to provide such feedback that will maximize performance.

International audience; Qui aurait imaginé il y a vingt ans que nous pourrions aujourd'hui visiter une ville en ayant dans notre poche un accès aux inventaires patrimoniaux des monuments et des oeuvres que nous avons sous les yeux ?Cependant, cette disponibilité de données de qualité ne garantit pas leur appropriation par les visiteurs qui leur préfèrent souvent les avis plus ou moins inspirés des visiteurs précédents. Comme nous le verrons sur un exemple issu du patrimoine vitré troyen, nous pensons que l'un des freins à l'utilisation in situ de ces descriptions est le type de modèle informatique utilisé : un modèle suffisamment raffiné pour combiner des termes (prédéfinis ou non) sous formes de scènes et de figures, mais qui vise à une universalité de la description, là où, au contraire, le sens émerge de ressemblances et de différences à l'échelle d'un territoire, d'un édifice ou même au sein d'une oeuvre ou d'une partie de cette oeuvre.Au fil de l'interprétation de ce vitrail, nous esquisserons les contours du modèle informatique que nous appelons de nos vœux, un modèle qui n'est pas sans rappeler celui de Xanadu, le projet initial de l'hypertexte qui visait à transformer les "calculateurs" en "machines [pour les] littéraires".

International audience; In the current study, we focused on decoding speech prosody from EEG. Prosody (i.e., melody and rhythm of speech) is important during communication as it allows to convey emotion and meaning. However, it has received little attention in the field of brain-computer interfaces. To address this issue, we contrasted the production of two syllables, "ba" and "da", produced mentally as an affirmation (e.g., "ba.") or a question (e.g., "ba?") using two different intonations. We focused on spectral features. After classification in the time-frequency domain, we found above chance-level accuracies in specific frequency ranges of the alpha band (7-12 Hz) early on during the production phase. We also obtained above chance-level results on a range of the low-beta band (16-20 Hz) during a late time window. Based on the visual inspection of topographies and the literature, we suggest that the results during the early time window, but not that during the late time window, reflect a genuine difference between imagined affirmation and question production. Future studies should provide more information about neural markers and underlying neuro-cognitive processes to improve the understanding of the imagined intonation production. This would pave the way for the development of speech-based BCI capable of differentiating intonation and prosody in general.

International audience; Today, we live in an age of 'Like' where appreciation of digital content is expressed constantly by interacting with feedback icons. In contrast, Brain-Computer-Interfaces (BCIs) can decode cognitive states from neural signals without explicit user feedback that interrupts aesthetic experiences (AEs). This recently started project will elucidate the neuro-cognitive mechanisms behind art appreciation and implement an Electroencephalography (EEG)-based BCI to detect physiological correlates of artwork preference in order to curate personalized art exhibitions in Virtual Reality. Most EEG recordings in visual neuroaesthetics focused on Event-Related Potentials, often using paradigms with unatural viewing conditions. On the other hand, the neural dynamics during visual art appreciation remain obscure and previous studies reported conflicting results. Furthermore, the liking of visual artworks was mostly investigated from the perspective of beauty or pleasantness, concepts which are not applicable to all aesthetic pleasures. We hypothesize instead that art preferences in general depend on rewarding AEs. Therefore, we will develop novel algorithms to decode and discriminate EEG neuromarkers of hedonic AEs. In a first step, we conceptualized neuro-cognitive components of AE, such as attention, emotion and intrinsic reward, as well as their established EEG neuromarkers. In the future, we will record EEG and other physiological measures, e.g. eye-tracking and heart rate, in naturalistic single trial experiments, use advanced Machine Learning to detect artwork preference and recommend further objects based on this multimodal information. Finally, we embrace open science and will make subject data and BCI algorithms publicly accessible.

Proceedings of the 19th Sound and Music Computing Conference -June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.fr

International audience; Improving user performances is one of the major issues for Motor Imagery (MI)-based BCI control. MI-BCIs exploit the modulation of sensorimotor rhythms (SMR) over the motor and sensorimotor cortices to discriminate several mental states and enable user interaction. Such modulations are known as Event-Related Desynchronization (ERD) and Synchronization (ERS), coming from the mu (7-13 Hz) and beta (15-30 Hz) frequency bands. This kind of BCI opens up promising fields, particularly to control assistive technologies, for sport training or even for post-stroke motor rehabilitation. However, MI-BCIs remain barely used outside laboratories, notably due to their lack of robustness and usability (15 to 30% of users seem unable to gain control of an MI-BCI). One way to increase user performance would be to better understand the relationships between user traits and ERD/ERS modulations underlying BCI performance. Therefore, in this article we analyzed how cerebral motor patterns underlying MI tasks (i.e., ERDs and ERSs) are modulated depending (i) on nature of the task (i.e., right-hand MI and left-hand MI), (ii) the session during which the task was performed (i.e., calibration or user training) and (iii) on the characteristics of the user (e.g., age, gender, manual activity, personality traits) on a large MI-BCI data base of N=70 participants. One of the originality of this study is to combine the investigation of human factors related to the user's traits and the neurophysiological ERD modulations during the MI task. Our study revealed for the first time, associations between ERD and both age, level of study, impression management and anxiety.

(1) Background: Insomnia is the most prevalent sleep disorder worldwide and cognitive behavioral therapy is the front-line treatment. Digital health technologies have a role to play in screening and delivering interventions remotely and without the need for human intervention. The KANOPEE app, which provides a screening and behavioral intervention for insomnia symptoms through an interaction with a virtual agent, showed encouraging results in previous studies during and after the COVID-19 lockdown, but has not yet been evaluated in a controlled study. This study aims at comparing the benefits of KANOPEE, a smartphone application dealing with insomnia complaints, with another application proposing an electronic sleep diary named “My Sleep Diary”. The acceptance and potential benefits of these digital solutions are tested in real-life settings (i.e., without soliciting human medical resources) and in the general population. (2) Methods: Subjects were included if they downloaded one of the apps between December 2020 and October 2021, and were of legal age. Both apps were available on downloading platforms in France. Primary outcome was Insomnia Severity Index (ISI), and secondary outcomes were total sleep time (TST), sleep efficiency (SE) and wake time after sleep onset (WASO). (3) Results: A total of 535 users completed the intervention with KANOPEE and 489 users completed My Sleep Diary, both for 17 days. KANOPEE users improved their ISI score significantly more than sleep diary users (interaction Time*Group: F(2,2002) = 17.3, p < 0.001). Similar results were found for nocturnal sleep parameters (TST) (KANOPEE users gained 48 min of sleep after intervention, while My Sleep Diary users gained only 16 min of sleep), and particularly in the population with moderate to severe initial sleep complaints (F(4,1980) = 8.9, p < 0.001). Other sleep markers (SE and WASO) were significantly improved in the KANOPEE users compared to the sleep diary ones (p < 0.001). (4) Conclusions: KANOPEE provides significantly greater benefits than an electronic sleep diary regarding reduction of insomnia complaints and estimated nocturnal sleep characteristics in a self-selected sample of the general population. Population with the most severe initial ISI score (≥15) benefited the most from the KANOPEE App compared to filling up a simple sleep diary.

International audience; Electroencephalogram (EEG) signals is recorded as a multidimensional dataset, which can be interpreted using autoregressive (AR) models. These models are based on the hypothesis that the signal can be explained by its past values and an additional random component called innovation. In this way, it is possible to extract relevant information about the signal, which can be used for a BCI classification. From the AR equation can be derived the Yule-Walker equations, which show the emergence of a symmetric positive definite matrices (SPD) matrix i.e. the autocorrelation matrix with lags. The state-of the art for classifying SPD matrices is based on Riemann Geometry, so a fairly natural idea is therefore to extend the standard approach using these autocorrelation matrices with lags. In order to validate the results, we test our approach both with a classification on the Riemann surface using the Minimum Distance to Mean and also with a classification on the Tangent Space using Support Vector Machine. To compute the hyper-parameters of the model, we use a Grid Search algorithm. The problem can also be formulated from another point of view: since the AR Yule-Walker matrix is a matrix of delayed correlations, we can obtain the same result by creating an embedding of the original system in a high dimensional space. Hence, it is natural to connect our approach with the delay embedding theorem proposed by Takens in the context of dynamical systems. Such an embedding method is based on the knowledge of two parameters: the delay parameter and the embedding dimension, respectively the lag and the order in the context of the AR model. This approach can be used as a new method to compute the hyper-parameters. We will test our approach on several dataset and on several subjects using the MOABB framework, using both within-session and cross-session evaluation.

International audience

In this paper we present Qed, a prototype programming environment for designing and performing temporal scenarios. Such scenarios can be used to trigger cues and control various parameters of live shows and interactive installations, such as audio and video playback, lights, or mechatronics. Qed features a structure editor operating on a syntax tree that intermingles textual tokens and graphical user interface elements. This allows specifying scenarios algorithmically using a domain specific language, while expressing continuous time transformations with graphical curves. Qed uses an imperative synchronous language to express concurrent poly-temporal scenarios. Scenarios are compiled on-the-fly into a bytecode that is run by a virtual machine. A temporal scheduler organizes the execution of concurrent parts of that bytecode along multiple abstract time axis, mapping abstract dates and delays of the program onto real time using a differential equation solver. The virtual machine feeds back execution information to the structure editor, which reflects that information by highlighting executed statements or displaying progress wheels and status icons directly in the code. This allows an operator to easily monitor and pace the progression of the scenario.

International audience; Housing under a shared housing organisation enables frail elderly persons to live in a semi autonomous way, thanks to cooperation between residents and an assistant. The social organization of this new type of housing also has an impact on the social participation of users. This article is based on a pilot study and deals with the benefits of digital technologies and “ambient intelligence” used to answer the needs of such a way of living. The pilot study was carried out in a house shared by 6 co-tenants. The qualitative method used first consisted in a characterisation of the 6 inhabitants. This was followed by semi-structured interviews about their sensed needs, and a focus group, with 5 of the 6 co-tenants, in order to gain an initial consensus about needs. This result was confronted to the demands of the assistants, collected through interviews. A usage scenario was developed in a smart home (Maison Intelligente de Blagnac). This scenario was performed by three of the inhabitants and followed by a second focus group and a narrative interview with the assistants and the designers of the shared house. This article reports the method which was carried out and the needs expressed by the co-tenants.

Rational drug design, as car or building design, implies a detailed understanding of proteins’ behavior. Proteins are the building blocks the workers, the messengers, the transporters involved in the cell machinery and its components, and targeted by drugs. However, one of the major obstacles to this approach lies in the limitations of the human-computer interfaces to manipulate complex, three-dimensional, flexible objects during a simulation in progress. To address this problem, we designed a tangible molecular interface, allowing the manipulation of a modular and �exible physical molecular model, to build and manipulate a virtual molecular twin from this physical model, synchronized thanks to embedded sensors. We propose to present this tangible interface, allowing to open the discussion on the perspectives concerning this prototype., Concevoir de manière rationnelle des médicaments, comme on conçoit une voiture ou un bâtiment, implique une compréhension fine du fonctionnement des protéines, protéines constituant les briques, les ouvriers, les messagers, transporteurs, nécessaires au fonctionnement de la cellule et de ses composants, et ciblées par les médicaments. Cependant, un des freins majeurs à cette approche appelée Rational Drug Design, réside dans les limitations des interfaces humain-machine pour manipuler des objets moléculaires, complexes, tridimensionnels et flexibles. Pour avancer sur cette problématique, nous avons conçus une interface tangible moléculaire, permettant la manipulation directe d’un modèle physique moléculaire modulaire et flexible, outillé par des capteurs électroniques, pour construire et manipuler le jumeau virtuel moléculaire de ce modèle physique. Nous proposons d’en faire la démonstration, en suscistant la discussion sur les perspectives d’évolution de notre prototype.

This demonstration aims at presenting ScenaProd, a tool that allows people to develop multisensory exercises. All participants will be able to create their own multisensory exercise with that tool. They will also have the possibility to test a more complete exercise that will already have been created. A multisensory exercise can be defined as an interaction between a human being and different devices. For example, a robot asks a question while displaying a visual clue on a screen. Then, the participant can respond by pressing a large and colored contactor. In case of a correct answer, the robot would play a short victory song and a light would light up green. If a wrong answer were given, the system would have a different reaction., Cette démonstration a pour objectif de présenter ScenaProd, un outil qui permet d’élaborer des exercices multi-sensoriels. Les participants pourront d’une part créer leur propre exercice multi-sensoriel avec l’outil et d’autre part, tester un exercice plus complet déjà créé. Un exercice multi-sensoriel est une interaction entre un humain et des périphériques. Par exemple, on pourrait définir qu’un robot pose une question tout en affichant un indice visuel sur un écran. Et le participant pourrait répondre en appuyant sur un gros contacteur coloré. Si la réponse est bonne, le robot pourrait jouer un petit son de victoire et une lampe d’ambiance s’allumerait en vert. Et si la réponse est incorrecte, alors le système aurait une réaction différente.

International audience; Motor Imagery-based BCI (MI-BCI) performances remain highly variable, with up to 30% of users unable to achieve control. Operating a BCI system requires users to learn to modulate their neural activity. This is a complex task, thus the training procedure is crucial. Our study draws on task-feedback transparency to improve the feedback given during training. MI-BCI protocols often feature abstract feedback (e.g., visual gauge) unrelated to the imagined movement. Transparent feedback, directly related to the task, may reinforce agency-the ability to self-attribute actions, such as feedback movements-and embodiment, facilitating kinesthetic MI. This could lessen complexity in BCI control and ultimately improve BCI performance.We tested this hypothesis in a beta-based MI neurofeedback task with electroencephalography (EEG). Twenty-three subjects participated in a single MIneurofeedback session that consisted in imagining clenching their right hand rhythmically. Feedback was based on online laplacian-filtered 8-30Hz power on C3 electrode computed with OpenViBE. There were 3 feedback conditions of expected increasing transparency: pendulum; virtual hand; virtual hand with additional motor illusion induced by vibrations to the participant's hand. The amplitude of the pendulum and virtual hand movements was proportional to beta desynchronisation. Each participant performed two runs of five 24s-trials per condition. Agency, embodiment, and user experience questionnaires were included. Repeated-measures ANOVA showed better BCI performance when using the virtual hand than the pendulum. However, participants had lower performance in the visuotactile condition compared to the virtual hand-only feedback. Agency showed a similar pattern.Feeling of success in the task did not vary with feedback conditions, but the virtual hand feedback felt easier to use. BCI performance correlated positively with agency for all conditions and with embodiment in conditions with a virtual hand.Thus, visual transparency—but not tactile feedback addition—increased BCI performance and this was associated with better agency and embodiment.

International audience; Stroke leaves around 40% of surviving patients dependent in their activities of daily living, notably due to severe motor disabilities [Inserm, 2019]. Brain-Computer Interfaces (BCIs) have been shown to be efficient for improving motor recovery after stroke [Cervera et al., 2018], but this efficiency is still far from the level required to achieve the clinical breakthrough expected by both clinicians and patients. While technical levers of improvement have been identified, they are insufficient: fully optimised BCIs are pointless if patients and clinicians do not want to use them [Blain-Moraes et al., 2012].We hypothesise that improving BCI acceptability and acceptance, by better informing stakeholders about BCI functioning and by personalising the BCI-based rehabilitation procedures to each patient, respectively, will favour engagement in the rehabilitation process and result in an increased efficiency.Our first objective was to identify the factors influencing the intention to use (IU) BCIs [Davis, 1989]. Based on the literature, we constructed a model of BCI acceptability and adapted it in questionnaires addressed to the general population (n=753) and post-stroke patients (n=33). Videos were included, one about the general functioning of BCIs, the second about their relevance for rehabilitation.We used random forest algorithms to explain IU based on our model's factors. After the first video, IU was mainly explained by subjective and personal factors, i.e., perceived usefulness (PU), perceived ease of use (PEOU) and BCI playfulness for the general population, and PU, autonomy and engagement in the rehabilitation for the patients. After the second video, the explanatory factors became more scientific/rational, with PU, cost-benefits ratio and scientific relevance for the general population, and PU, scientific relevance and ease of learning for patients.The shift of main explanatory factors (before/after second video) from subjective representations to scientific arguments highlights the impact of providing patients with clear information regarding BCIs.

International audience; In this study, we expand upon recent evidence that the motion of virtual characters affects the proximity of users who are immersed with them in virtual reality (VR). Attractive motions decrease proximity, but no effect of character gender on proximity was found. We designed a similar experiment where users observed walking motions in VR which were displayed on male and female virtual characters. Our results show similar patterns found in previous studies, while some differences related to the model of the character emerged.

Human motor adaptation is crucial to remain efficient when exposed to unfamiliar environments. In these contexts, the efficient strategies developed by the brain to optimise movement can prove deficient. Dexterous manual movement execution in space therefore require the learning of new coordinated motor actions. Traditionally, adaptation mechanisms are tested in laboratory using robotic devices that disturb the limb specifically involved in the task while the dynamics of the rest of the body remain unchanged. Although participants build a more accurate representation of the task over repetitions, these approaches are limiting as they do not reflect the ecological adjustment to globally modified dynamics. The aim of this doctoral dissertation is to better understand basic motor adaptation and to provide useful information for developing solutions that optimise actions when faced with a constraining environment. To do this, we first aimed to characterize gravity integration within the central nervous system. Then, we tested the impact of local gravity compensation while the rest of the body is immersed in an extreme environment (0 and 1.8g, induced in parabolic flight). To this end, we designed a motorised system that locally recreates terrestrial sensory information (1g) at the level of the limb involved in a simple pointing task. Our results suggest that the addition of known information helps to improve motor performance in unusual contexts. By adopting the “negative image” of conventional robotic approaches, our experiments tend to provide effective information for the design of useful interfaces for humans facing altered environments; thus opening up the scope of possibilities., L'adaptation motrice humaine est cruciale pour rester efficace en cas d’exposition à des environnements inconnus. Dans ces contextes, les stratégies efficaces développées par le cerveau pour optimiser les mouvements peuvent être mises en défaut. La manipulation manuelle et les mouvements fins dans l'espace nécessitent donc l'apprentissage de nouvelles actions motrices coordonnées. Traditionnellement, les mécanismes d'adaptation sont testés en laboratoire à l'aide de dispositifs robotisés qui perturbent le membre impliqué spécifiquement dans la tâche alors que la dynamique du reste du corps demeure inchangée. Bien que les participants construisent une représentation plus précise de la tâche au fil des répétitions, ces approches sont limitatives puisqu'elles ne reflètent pas l'ajustement écologique à des dynamiques globalement modifiées. Ce travail doctoral a pour objectif de mieux comprendre l'adaptation motrice de base et tend à fournir des informations utiles pour développer des solutions afin d’optimiser les actions de l’individu lorsque celui-ci est confronté à un environnement contraignant. Pour cela, nous avons tout d’abord caractérisé l’intégration de la gravité au sein du système nerveux central. Ensuite, nous avons testé l’impact d’une compensation en gravité locale alors que le reste du corps est immergé dans un environnement extrême (0 et 1.8g, induits en vol parabolique). Pour ce faire, nous avons conçu un système motorisé qui recrée localement des informations sensorielles terrestres (1g) au niveau du membre engagé dans une tâche simple de pointage. L’ensemble de nos résultats suggèrent que l'ajout d'informations connues aide à améliorer la performance motrice dans des contextes inhabituels. En adoptant « l'image négative » des approches robotiques conventionnelles, nos expérimentations tendent à fournir des informations profitables pour la conception d’interfaces utiles pour l’Homme confronté à des environnements altérés ; ouvrant ainsi le champ des possibles.

Previous studies about kinesthetic expressions of emotions are mainly based on acted expressions of emotions, which can be quite different from spontaneous expressions. This paper describes a study involving a stress induction procedure and stress perception through haptic expressions with N $_{\mathrm{total}}$ total = 41 young men (aged $19 - 37$ 19 - 37 ), all right-handed. We designed a game application to collect spontaneous expressions of stress. This application involved haptic interactions and a stressful event. We observed changes in the haptic behaviors of the participants over different phases: before, during and after the stress induction. In the next step, we investigated how the collected haptic behaviors (both kinematic and force components) were haptically perceived by the other participants. The results suggest the ability of kinesthetic expressions to communicate a spontaneous stress from one person to another.

We report preliminary results to automatically identify effective tactics of elite table tennis players. We define these tactics as subgroups of winning strokes that table tennis experts seek to identify in order to train players and adapt their strategy during play. We first report how we identify and classify these subgroups using the weighted relative accuracy measure (WRAcc). We then present the subgroups using visualizations to communicate these results to our expert. These exchanges allow rapid feedback on our results and makes it possible further improvements to our discoveries.

Teaching a language does not only include linguistic structures, but also the culture linked to it. In the context of French as a foreign language, it is important to highlight the cultural elements linked to France and other Frenchspeaking countries. For our thesis work, we are developing a serious game for foreign students at the University of Orléans who wish to continue their studies in France. It is therefore essential to include references to popular culture. At the same time, we taught refugees at Sciences Po Paris, who also wanted to study and work in their host country. Regarding the latter, it seemed essential to us to consolidate their integration, taking care that they do not deny their origins and their identity. Our work will therefore focus on the mechanisms facilitating a balanced cultural contribution in the learning of French., Enseigner une langue n’inclut pas uniquement les structures linguistiques, mais également la culture liée à celle-ci. Dans le cadre du Français Langue Etrangère, il est important de mettre en avant les éléments culturels liés à la France et aux autres pays francophones. Pour notre travail de thèse, nous concevons un jeu sérieux à destination des étudiants étrangers de l’université d’Orléans qui souhaitent poursuivre leurs études en France. Il est donc primordial d’y inclure des références à la culture populaire. En parallèle, nous avons enseigné à des réfugiés à Sciences Po Paris, qui avaient aussi pour objectif d’étudier et de travailler dans leur pays d’accueil. Concernant ces derniers, il nous a semblé essentiel de consolider leur intégration, en faisant attention à ce qu’ils ne renient pas leurs origines et leur identité. Notre travail portera donc sur les mécanismes facilitant un apport culturel équilibré dans l’apprentissage du français.

Wearable sensing technologies allow us to monitor and track a wealth of information about bodily states. Tracking applications rely on abstract numerical or graphical visualizations to make this information accessible to us. However, these visualizations can be hard to interpret, and even be harmful to already vulnerable groups. Hence, we propose to give feedback in the form of an enhanced heart rate interoception and an embodied artificial agent. This method relies on the person’s inherent understanding of their own body. It is a subtle and more natural way to gauge the meaning of off-the-shelf sensors’ feedback. A wearable pet prototype that presents emotion through visuo-haptic feedback is evaluated in a match and a mismatch group. Participants in both groups answered self-report and perceived affect of the interoceptive feedback without significant differences. However, the groups’ perceived closeness to the pet differed significantly.

While domain characterization has become an integral part of visualization design studies, methodological prescriptions are rare. An underrepresented aspect in existing approaches is domain expertise. Knowledge elicitation methods from cognitive science might help but have not yet received much attention for domain characterization. We propose the Critical Decision Method (CDM) to the visualization domain to provide descriptive steps that open up a knowledge-based perspective on domain characterization. The CDM uses retrospective interviews to reveal expert judgment involved in a challenging situation. We apply it to study three domain problems, reflect on our practical experience, and discuss its relevance to domain characterization in visualization research. We found the CDM's realism and subjective nature to be well suited for eliciting cognitive aspects of high-level task performance. Our insights might guide other researchers in conducting domain characterization with a focus on domain knowledge and cognition. With our work, we hope to contribute to the portfolio of meaningful methods used to inform visualization design and to stimulate discussions regarding prescriptive steps for domain characterization.

Background: Mobility-as-a-Service (MaaS) is a new concept based on shared mobility. The concept of MaaS is to use one single application of mobility to access and pay for various transport modes. The adoption of the application by users is a new challenge for cities, especially because it allows to promote sustainable modes of transport. Individual car is one of the main transport modes used by citizens, while bike-sharing is the least used mode of transport (Nikita, 2018). The information provided by the application can influence travel behavior in the choice and planning of their daily mode of transport (Lyons et al., 2019). Factors like expected travel time, reliability of availability information, and uncertainty about the availability of bike are considered to be an essential information prerequisite for users to travel with shared bike (Van Hagen & Bron, 2013; Lamborton & Rose, 2012). Other innovative factor as gamification start to be investigated by researchers, especially due to their great influence on the choice of sustainable mode of transport (Yen et al., 2018). The aim of the present study is thus to examine the effects of travel time, of reliability of information displayed by the app, of information of availability verified by others users, and of gamification on the intention to use a shared bike instead of an individual car. Method: Participants were French-speaking volunteers (from 18 years old). They were exposed to 24 scenarios built following Anderson’s methodology (2013). In each scenario, a character had to plan a commute to work using an application for mobility within his city. The application gave the user the choice to use a bike-sharing solution or their own individual car to go to work. In each scenario, different combinations of conditions changed (expected travel time: reduced, no change, increase; reliability of information: no reliable; reliable; information of availability verified by others users: verified by other users, no verified by other users; gamification: gains of points, no gain). Using a within-participants protocol, participants were asked to rate their intent to use a bike-sharing solution instead of their individual car as if they were the protagonists. Data collection is ongoing and results will be presented at the conference. Expected results: We predict that the increase of travel time, the unreliability and the uncertainty of availability of bike, increase the intention to no use a bike-sharing. We hypothesize that the gain of points increases the intention to use a bike-sharing. We expect that the gain of points should mitigate the no use of the bike by increasing the intent to use a bike-sharing instead of individual car (Giovina Pasca et al., 2020). Discussion: The results will be discussed in line with recent studies about MaaS application and knowledge about bike-sharing demand. Moreover, as explained by Fishman (2015), previous studies tend to research with large number of people who are not shared-bike users. Understanding also the perceptions of non-users will be a topic for further research. A complementary cluster analysis will allow to better understand if the results also needed to be interpreted in relation to the user’s profile (age, profession, frequency of bike use, etc). These findings will be used to preconize recommendations for the design of future applications for mobility.

International audience; A key challenge when studying human-agent interaction, is the evaluation of user's experience. In virtual reality, this question is addressed through the study of the sense of presence and copresence, generally assessed thanks to well-grounded subjective post-experience questionnaires. In this article, we aim at correlating objective multimodal cues produced by users to their subjective sense of presence and co-presence. Our study is based on a human-agent interaction corpus collected in task-oriented context: a virtual environment aiming at training doctors to break bad news to a patient played by a virtual agent. Based on a corpus study, we have used machine learning approaches to explore the possibility of automatically predicting the sense of presence and co-presence of the user thanks to specific multimodal behavioral cues. The performance of random forests models demonstrates the capacity to automatically and accurately predict the level of presence. It also shows the relevance of a multimodal model, based on verbal and non-verbal behavioral cues as objective measures of presence.

Several studies have presented trust as crucial to predict AI acceptability. We aim to involve statistical and social measures of trust, to confirm links between trust and acceptability, and between trust and emotional variation, with an experimental protocol inspired by [1]. Sixty participants are asked to estimate ages on portraits; then, an AI model suggests its own prediction based on facial features, along with its stated confidence. Participants can then keep or change their initial prediction. Three measures are used to quantify their confidence in the model: the proportion of agreements and changes, and fixation duration. Participants are also asked to complete a questionnaire to measure their trust and acceptance, and their facial expressions are recorded during the experiment to assess emotional variation. Therefore, this research allows to better understand links between trust, emotions, and acceptability in AI., Diverses études présentent la confiance comme essentielle pour tirer profit des solutions d’IA, et comme prédictive de son acceptabilité. Notre étude a pour objectif de mobiliser des mesures statistiques et sociales de la confiance, de réaffirmer les liens entre confiance et acceptabilité, et entre confiance et variation émotionnelle. Cet abstract présente le protocole expérimental mis en place, inspiré par [ 1]. Des portraits sont présentés à 60 participants, devant estimer leur âge ; puis un modèle IA propose sa propre prédiction à partir de caractéristiques faciales, ainsi que sa confiance déclarée. Les participants ont alors le choix entre conserver leur prédiction initiale ou changer de réponse. Pour mesurer le comportement des participants, nous récoltons les proportions d’accords et de changements face aux prédictions du modèle, et nous enregistrons le temps des fixations oculaires et leurs expressions faciales. Les participants remplissent également un questionnaire pour mesurer leur confiance et acceptation dans le modèle. Cette recherche nous permet ainsi de mieux comprendre les liens entre confiance, variation émotionnelle, et acceptabilité en l’IA.

Human-aware and so-called social navigation abilities of a robot need to be tested and evaluated in real-life experiments with real humans. Such tests are mandatory to validate a mature system. But they are heavy to set up and can become tiresome when debugging the early stages of a system. Simulation could help solve this issue, but the lack of available intelligent human avatars that can exhibit a rational behavior restricts this to simple scenarios. To address this issue, we propose a system providing first an autonomous intelligent human agent specifically designed to act and interact with a robot navigating in a simulated environment. Then, the system provides a GUI to visualize the paths taken by the agents as well as the produced metrics in order to help evaluate the interaction. Moreover, the system also provides a high-level interface to control the agents and run repeatable scenarios. We show through a set of experiments how the proposed system can help answer the lack of intelligent avatars for tuning and debugging social navigation systems before their final evaluation with real humans.

In this paper, I relate an auto-reflexive analysis of my practice of designing and musicking deep reinforcement learning. Based on technical description of the Co-Explorer, a deep reinforcement learning agent designed to support sonic exploration through positive or negative human feedback, I discuss how deep reinforcement learning can be seen as a form of sonic comprovisational agent, which enables musicians to compose a parameter sound space, then to engage in embodied improvisation by guiding the agent through sound space using feedback. I then relate on my own musicking experiments led with the Co-Explorer, which resulted to the creation of the ægo music performance, and build on these to sketch a music representation for deep reinforcement learning, highlighting its original aesthetics, as well as its ontological shifts between performer and agent, and epistemological tensions with engineering-oriented representations. Rather than discrediting the latters, my wish is to create space for practice-based approaches to machine learning in a way that is complementary to engineering-oriented approaches, while contributing to further music representations and discourses on artificial intelligence.

The goal of this workshop is to discuss the potential benefits and the open challenges of giving a physical form to Artificial Intelligence (AI), towards the definition of tangible, or graspable AI. In the workshop we will focus on the use-case of a convolutional Neural Network for image analysis and we will carry out a hands-on paper prototyping activity to imagine tangible interactive AI-powered systems where critical parameters of the Neural Network are physicalized. Such systems have the potential to lower the barrier for AI education and for making AI systems more trustable and explainable

L'intégration des réfugiés dans un pays d'accueil commence par l'apprentissage de la langue, mais aussi par la découverte des différences culturelles. Si l'on souhaite faciliter leur installation, il est nécessaire d'adapter l'enseignement afin qu'ils puissent acquérir la maîtrise des mots et des nouvelles mœurs, tout en conservant leur identité.

An ever-increasing number of human-machine interfaces have embraced touchscreens as their central component, such as in smartphones, laptops, terminals, etc. Their success has been particularly noticeable in the automotive industry, where physical buttons have been replaced by touchscreens to handle multiple elements of the driving environment. However, contrary to physical buttons, these interfaces do not possess any tangible elements that allows the user to feel where the commands are. Without tactile feedback, users have to rely on visual cues and simple adjustment tasks become significant distractions that may lead to dangerous situations while driving.Recently, haptic touchscreens have emerged to restore tangibility to these interfaces, by rendering the sensation of feeling textures and shapes through friction modulation. However, we still do not have a good understanding of how these synthetic textures are perceived by humans, which is crucial to design meaningful and intuitive haptic interfaces.In this thesis, I first show that the perception thresholds of friction modulated textures are similar to vibrotactile thresholds. Then, I investigate the perception of haptic gradients, i.e., textures whose spatial frequency gradually changes. Hence, a law that describes the minimal exploration distance to perceive a given gradient is deduced. This law is similar to the auditory perception of rhythm variations, which suggests that there are common mechanisms between the two modalities. Finally, I demonstrate that gradient haptic feedback can guide a user to adjust a setting on an interface without vision.The findings shed new light on the understanding of haptic perception and its multisensory interactions and open up new possibilities in terms of human-machine interaction., Les écrans tactiles ont envahi notre quotidien et sont maintenant présents dans un grand nombre d'appareils tels que les téléphones, les ordinateurs, les bornes de commande, etc. Leur succès a aussi gagné l'industrie automobile, où les écrans ont remplacé les boutons physiques pour gérer les paramètres de l'environnement de conduite. Cependant, contrairement aux boutons physiques, les interfaces sur écran tactile ne possèdent pas d'éléments tangibles permettant à l'utilisateur de sentir les commandes. Sans retours tactiles, les utilisateurs ne peuvent se fier qu'aux indications visuelles et de simples tâches de réglage peuvent devenir des distractions importantes au volant.Récemment, les écrans haptiques ont fait leur apparition pour redonner une certaine tangibilité à ces interfaces en permettant de procurer des sensations de texture et de relief à leur surface grâce à la modulation de frottement. Cependant, nous ne comprenons toujours pas bien comment ces textures synthétiques sont perçues par l’homme, ce qui est une question cruciale pour concevoir des interfaces haptiques pertinentes et intuitives.Dans cette thèse, je montre tout d’abord que les seuils de perception des textures par modulation de frottement sont similaires aux seuils de perception des vibrations. Ensuite, j’étudie la perception des gradients haptiques, des textures dont la fréquence spatiale évolue progressivement. Il en ressort une loi décrivant la distance minimale d’exploration pour percevoir un gradient donné. Cette loi se révèle similaire à la perception auditive des variations de rythme, ce qui suggère qu’il existe des mécanismes communs entre les deux modalités. Enfin, je démontre que les retours haptiques de type gradient peuvent guider un utilisateur pour lui permettre d’ajuster un paramètre sur une interface sans recourir à la vision. Ces résultats apportent un éclairage nouveau sur la compréhension de la perception haptique et ses liens avec la perception auditive, et ouvrent de nouvelles possibilités en termes d’interaction homme-machine.

People with visual impairments are increasingly using smartphones, taking advantage of their accessibility tools, which are constantly being enhanced to meet their individual needs and preferences. However, in the public sphere these people are confronted with the use of products and services through touchscreens, often not adapted to their disability. These touchscreens, designed to offer a richer and more personalized interaction to users, impose accessibility constraints and barriers to the visually impaired. Among these services, payment is one of the most essential and critical. We conducted a series of user interviews to understand the issues that visually impaired people face on a daily basis with public touchscreens, focusing more deeply on touch payment terminals. Based on the results of these interviews, we designed and developed a proof of concept (Worldline Accessibility Remote) where the smartphone is used as an accessibility tool to interact with the Worldline YUMI touch payment terminal. Finally, we conducted user tests to evaluate the acceptability and usability of our solution., Les personnes à déficience visuelle utilisent de plus en plus les smartphones tirant profit de leurs outils d’accessibilité qui ne cessent de s’enrichir pour répondre à leurs besoins et préférences individuels. Cependant, dans la sphère publique ces personnes sont confrontées à l’utilisation de produits et de services au travers d’écrans tactiles, bien souvent non adaptés à leur handicap. Ces écrans tactiles, conçus à la base pour offrir une interaction plus riche et personnalisée aux utilisateurs, imposent aux déficients visuels des contraintes et des barrières d’accessibilité. Parmi ces services, le paiement est l’un des plus indispensables et critiques. Nous avons mené une série d’entretiens utilisateurs pour comprendre les problèmes que les déficients visuels rencontrent quotidiennement avec les écrans tactiles publics en s’intéressant plus profondément aux terminaux de paiement tactiles. En se basant sur les résultats de ces entretiens, nous avons conçu et développé une preuve de concept (Worldline Accessibility Remote) où le smartphone est utilisé comme un outil d’accessibilité pour interagir avec le terminal de paiement tactile YUMI de Worldline. Nous avons enfin réalisé des tests utilisateurs pour évaluer l’acceptabilité et l’utilisabilité de notre solution.

International audience; Neurofeedback training (NFT) describes a closed-loop paradigm in which a subject is provided with a real time evaluation of his/her brain activity. As a learning process, it is designed to help the subject learn to apprehend his/her own cognitive states and better modulate them through mental actions. Its use for therapeutic purposes has gained a lot of traction in the public sphere in the last decade, but conflicting evidence concerning its efficacy has led to a two-pronged effort from the scientific community. First, a call for experimental protocols and reports standardization [1], aiming to reduce the variability of the results and provide a reliable set of data to describe empirical findings. Second, an effort towards a formal description of the neurofeedback loop and the main hypotheses that guide the design of our experiments, in order to explain or even predict the effects of such training [2,3].

Flying drones is an increasingly popular activity. However, it is challenging due to the required perceptual and motor skills for following and stabilizing the drone, especially for people with special needs. This paper describes CandyFly, an application supporting people with diverse sensory, cognitive and motor impairments to pilot drones. We observed an existing accessible piloting workshop and evaluated CandyFly during eight additional workshops over three and a half years using a research-through-design process and ability-based design methods.We identified users' needs, formulated requirements and explored adaptive interactions such as using pressure-sensitive keys, adjusting controls to the pilots’ range of motion, or limiting the drone’s degrees of freedom to cope with a broad range of disabilities.Our results show that the pilots and their caregivers enjoyed flying and emphasized CandyFly’s ability to be tailored to specific needs. Our findings offer a framework for designing adaptable systems and can support the design of future assistive and recreational systems.

The LexiKHuM project (Human-Machine Kinesthetic Lexicon) [1] studies and develops kinesthetic communication solutions for human-machine interaction. Our objective is to implement a kinesthetic lexicon that will be held on a haptic device for human-machine communication. We therefore explore human gestuality (both co-verbal gesture [CVG] and sign language [SL]) to extract features which can be reinvested in the kinesthetic lexicon, in order to ensure its closeness to natural language. One of the features we would like to introduce in our system is the epistemic dimension of the messages transmitted toward the human being, and thus the degree of certitude of the machine [2].For this purpose, we have gathered the articulatory and phonetic properties of the epistemic gesture in CVG and SL. Previous studies have shown that the head is an epistemic marker and its articulatory characteristics express the different degrees of certitude. For example, in German and Turkish SL, the extent of certitude is expressed by rapid head nods and the incertitude by slow head tilts and nods [3-4]. Similarly, in French, English and Catalan CVG, the degree of certitude is marked by a clear and strong nod of the head, and the incertitude by a tilt [5-6-7-8].We hypothesized that it is possible to identify in these head movements – just broadly described in the literature – some sub-parametric articulatory features which carry epistemic meaning. We thus propose to identify these traits through the study of a corpus of French CVG and SL [LSF], based on an analysis grid of the articulatory characteristics of these movements resulting from previous works [9-10-11-12-13]. Thereafter, we will show how these traits can be used to build a kinesthetic lexicon as close as possible to the natural language. This work is the precursor of a larger study on the identification of epistemic sub-parametric traits which are also present on other articulators.References:[1] LexiKHuM project (2021-2025). https://anr.fr/Projet-ANR-20-CE33-0012[2] Gosselin L. (2015). De l’opposition modus / dictum à la distinction entre modalités extrinsèques et modalités intrinsèques. Bulletin de la Société de Linguistique de Paris, CX-1: 1-50.[3] Herrmann A. (2013).Modal and focus particles in Sign Languages: across-linguistics study. De Gruyter Mouton (Berlin/Boston).[4] Karabüklü S., Bross F., Wilbur R., Hole D. (2018). Modal signs and scope relations in TİD. Proc. FEAST: Formal and Experimental Advances in Sign language Theory, 2: 82-92.[5] Roseano P., González M., Borràs-Comes J., Prieto P. (2016). Communicating epistemic stance: how speech and gesture patterns reflect epistemicity and evidentiality. Discourse Processes, 53: 135-174.[6] Borràs-Comes J., Kiagia E., Prieto P. (2019). Epistemic intonation and epistemic gesture are mutually co-expressive: empirical results from two intonation-gesture matching tasks. Journal of Pragmatics, 150: 39-52.[7] Ferré G. (2012). Functions of three open-palm hand gestures. Multimodal Communication, 1: 5-20.[8] Debras C. (2017). The shrug: forms and meanings of a compound enactment. Gesture, 16(1): 1-34.[9] Puupponen A., Wainio T., Burger B., Jantunen T. (2015). Head movements in Finnish Sign Language on the basis of motion capture data: a study of the form and function of nods, nodding, head thrusts, and head pulls. Sign Language & Linguistics, 18: 41-89.[10] Wilbur R.B., Malaia E. (2018). A new technique for analyzing narrative prosodic effects in sign languages using motion capture technology. in: Hübl A., Steinbach M. [eds], Linguistik Aktuel - Linguistics Today, 247: 15-40.[11] Boutet D. (2018). Pour une approche kinésiologique de la gestualité. HDR, Université de Rouen.[12] Catteau F. (2020). Traduire la poésie en langue des signes : l’empreinte prosodique lors du changement de modalité. PhD dissertation, Université Paris 8.[13] Chevrefils L., Danet C., Doan P., Thomas C., Rébulard M., Contesse A., Dauphin J.-F., Bianchini C.S. (2021). The body between meaning and form: kinesiological analysis and typographical representation of movement in Sign Languages. Languages and Modalities, 1: 49-63.

In the PRIM project, we aim at giving people the power to create scenagrams (interaction scenarios between a human and digital devices) without the need to learn programming or to ask for computer scientists. In this project, software design follows an unconventional approach, far from classical codes, to embody human thinking (based on interactions) instead of computer logic (based on algorithms). The main idea rests on a new time representation using a PRIM-specific timeline instead of a standardized timeline. We evaluated acceptability and cognitive compatibility of this new timeline with 50 participants. Results are very promising. In this paper, we detail qualitative evaluation results about the interest of such software in the field of disability., Avec le projet PRIM, nous souhaitons permettre à des personnes de créer des scénagrammes (scénarios d'interaction entre un humain et des dispositifs numériques) sans devoir se former à la programmation ou faire appel à des informaticiens. Dans PRIM, la conception du logiciel renverse les codes classiques dans le sens où il représente la pensée de l'humain (fondée sur les interactions) plutôt que la logique de l'ordinateur (fondée sur l'algorithmique) grâce à une représentation renouvelée du temps, abandonnant la timeline normée pour une timeline modifiée, propre à PRIM. Après avoir évalué l'acceptabilité et la compatibilité cognitive de cette timeline par 50 participants et obtenu des résultats encourageants, nous présentons, dans ce papier, les résultats de l'évaluation qualitative de l'intérêt d'un tel outil pour les participants et, plus spécifiquement, dans le domaine du handicap.

This paper presents and evaluates a new security primitive in the form of non-transferable ``visual secrets''. We show how they can be used in the design of voting systems. More specifically, we introduce a receipt-free low-tech visually verifiable boardroom voting system which is built for simplicity and can serve as a teaching tool to introduce people to verifiable voting. Visual secrets rely on the pre-semantic treatment of images in the human brain. After being shown an image for a limited time, users can recognise it in a larger set (79% recognition compared to an expected baseline of 5%). However, they cannot reliably communicate to someone else exactly how to do so (whether voluntarily or through coercion). Indeed, no assessor managed to accurately identify the images from the description given by the subjects. We then introduce a boardroom voting system based on this primitive. The voter receives a ballot consisting of a single picture, votes by folding it horizontally or vertically and casts it. If the voter is coerced into describing their ballot, several ballots are likely to correspond to the description. When all ballots are revealed, the voter can check with a glance that their ballot is present and folded correctly. This gives them the opportunity to detect error or fraud, although they cannot prove that fraud happened (the limited dispute resolution mechanism mainly focuses on incentives). The design makes use of textured paper to provide both accessibility for the blind and improved usability for all users.

International audience; Collaborative serious games have proven to be effective learning environments to enhance the development of learners' soft skills, such as collaboration, negotiation and cooperation. To be effective, such role paying games should provide genuine interactions. However, little is known on how design choices, such as the viewpoint (either first or third person perspective), impact collaborative processes and learners' perception of their partners. This paper reports an exploratory study on the impact of the viewpoint on the sense of social presence, and on collaborative processes that emerge from learners' interactions in a collaborative serious game dedicated to soft skills training. To address this issue, learners played in either first-person or third-person perspective during a session of two games. Our results show that the first-person view allowed for a higher sense of social presence and increased information sharing. This seems to be mainly due to the knowledge asymmetry caused by the affordances of the environment, in other words design choices. These results can be applied in the design of collaborative serious games that support social interactions and collaborative skills training.