What I do

My research interests include Human-Computer Interaction, Information Visualization and Data Analysis, User Experience Modeling, Reflective technologies, Interpretation systems, or Document and Knowledge Engineering. Application domains are related to education, culture, health, humanities… I focus on interdisciplinary approaches for the study of human-machine coupling and co-development and collaborate with people from sociology, psychology, ergonomy, anthropology, education science, philosophy, design, medecine, focusing on real world activities.

News (all)

Aug. 24: Publication of our paper on comparing patient experiences in VR and Reality. Our paper with Jean-Philippe Rivière and Louis Vinet about the OPEVA project has been published in the International Journal of Human-Computer Studies. In this paper entitled Towards the use of VR prototypes in architecture to collect user experiences. An assessment of the comparability of patient experiences in a virtual and a real ambulatory pathway, we explore if the experiences lived by patients in an immersive VR simulation of an ophthalmology ambulatory pathway are comparable to those they live in the real pathways. We show that patients live comparable experiences along various experiential dimensions such as thought, emotion, sensation, social and sensory perceptions, and that VR prototypes may be adequate to assess issues with architectural design. This work was conducted at Clinique Jules Verne in Nantes.

Apr. 24: Publication of our paper on Affordances research. We published a paper we had ben working on for a long time with Roman Malo. The paper is entitled Reaching conceptual stability by re-articulating empirical and theoretical work on affordances and has been published in Frontiers in Psychology. In this paper we claim that affordances lack conceptual clarity, that only empirical work can help settle on important theoretical questions, but also that theoretical and empirical research on affordances are disarticulated. Thus is because empirical work does not take into account current theoretical propositions and theoretical researchers do not seem interested in empirical verifications of their proposals. Yet the concept of affordance remains important for 4E cognition development, as well as a boundary objects for many other research fields. We then claim that it is important to re-articulate theoretical and empirical work, notably by fostering empirical studies, and we propose a set of requirement and a framework to develop adequate empirical methodologies.

Apr. 24: Presentation at the EMRN Conference. I presented a paper entitled “Towards immersive teleclinics in the Metaverse, the case of neuropsychological consultation” at the European Metaverse Research Network conference in Barcelona. The paper is co-authored with Toinon Vigier Didier Acier Samuel Bulteau and Solene Thevenet. It presents our work on the TECNIS (Téléclinique Immersive) project between Nantes Université and CHU de Nantes where we explore how social VR could be used for teleconsultation between a clinician and a patient, here in the case of neuropsychological testing. We decided that the practitioner should lead the session, that there should be two types of tests (desk-based and in independant environments), and we even developed a waiting room for the patient to wait for the doctor. The evaluation of the system is currently carried out, focusing on acceptability for patients and clinicians. This work participates to defining how we can leverage the Metaverse for future health. We are looking for collaboration for the next steps!

Recent publications (all)

Yannick Prié, Toinon Vigier, Didier Acier, Hélène Bonneville, Manon Georges, Solène Thevenet, Samuel Bulteau. (2025) A teleclinic for Neuro-psychological Assessment in the Metaverse in 32nd IEEE Conference on Virtual Reality and 3D User Interfaces, IEEE VR 2025, Mar 2025, Saint-Malo, France, 2pp. Show abstract Metaverse technologies allow new tele-medicine services and applications. Our interdisciplinary team conducted a user-centered design process, and implemented an immersive teleclinic for clinicians to carry out neuro-psychological testing sessions with distant patients. A session is a mix of discussions and desk-based or independent test activities, accompanied and monitored by the clinician with various dashboards. We carried out a preliminary evaluation focusing on usability, presence and acceptability for healthy participants playing the role of patients and practitioners. Results shows all could project into using the system, but practitioners were more reluctant, due so some usability issues, and insufficient quality of current technology to observe patients.

Majd Bitar, Jean-Philippe Rivière, Rebecca Fribourg, Jean-Marie Normand, Yannick Prié. (2025) Sustaining the Experience of Pair Natural Walking in Social Virtual Reality in 3rd Workshop on Locomotion and Wayfinding in XR (LocXR), at IEEE VR 2025, Mar 2025, Saint-Malo, France. Show abstract Walking together is a basic social interaction, making it an essential feature to support in social virtual reality. Most research on locomotion in VR focuses on the motor aspect of walking, rather than on the cognitive or social aspects of social walking. In this paper, we explore walking in pairs, draw on observations from a pilot study, and propose some recommendations for enhancing the experience of pair walking in social VR. We implemented two features based on the use of movement rhythm using arm-swinging locomotion and an aura to enhance the awareness of one’s partner walking, that we tested in a custom virtual environment. The initial results highlight the potential benefits of our proposals, yet future work is needed to strengthen these findings.

Pierre Vaslin, Yannick Prié. (2025) Informal skill-sharing in collaborative immersive analytics in IEEE Transactions on Visualization and Computer Graphics, to appear. doi Show abstract Newcomers to immersive analytics systems would benefit from informally learning data analysis skills (e.g. reading a vis, using a system) when collaborating with more expert participants. We want to design tools that facilitate this informal learning by encouraging the informal sharing of data literacy skills during collaborative immersive analysis. A first step toward this goal is to understand how informal skill sharing takes place in order to identify how it could be improved. We experimentally studied informal skill-sharing in pairs of participants analyzing scatterplots in a shared virtual reality environment. We used an original mixed-method to analyze video and log recordings as well as subjective experiential data, based on common ground theory and the grounding process. We uncovered 101 episodes of skill-sharing, organized in 14 recurring types, and identified associated problems from which we could propose six implications for designing systems that favor informal skill-sharing, hence skill learning. The method can be used to study informal skill sharing in other systems enabling embodied face-to-face collaboration, but would need to be simplified for large-scale use.

Victor Duvivier, Matthieu Perreira Da Silva, Yannick Prié. (2025) A conceptual framework for immersive behavioral data exploration assisted by a deep learned representation of data in IEEE AIxVR 2025 — 7th IEEE International Conference on Artificial Intelligence & eXtended and Virtual Reality, Jan 2025, Lisboa, Portugal, 5pp. Show abstract By allowing to conduct experiments involving ecologically valid tasks within controlled environments, Virtual Reality (VR) offers novel opportunities for studying human behavior. Several modalities can be leveraged, including event logs, motion trajectories, eye-tracking data, or physiological signals. However, analyzing such multimodal data presents considerable challenges due to their inherent complexity, the varied structures they imply, as well as the necessity to use exploratory approaches. There is therefore a need to design visual analytics tools for the exploration of immersive behavioral data without prior knowledge. Our idea is to integrate deep learned computational models —which leverage advanced techniques to extract valuable high-level features from unlabeled data— into exploratory Visual Analytics tools. We introduce a conceptual framework for integrating deep learning models into the Visual Analytics process of immersive behavioral data analysis, also focusing on the services that such systems should provide to the analysts.