RESEARCH CENTRE

Inria Centre
at the University of Bordeaux

2023
ACTIVITY REPORT

IN PARTNERSHIP WITH:

Université de Bordeaux, CNRS

Project-Team

POTIOC

Novel Multimodal Interactions for a
Stimulating User Experience

IN COLLABORATION WITH: Laboratoire Bordelais de Recherche en
Informatique (LaBRI)

DOMAIN

Perception, Cognition and Interaction

THEME

Interaction and visualization

Contents

Project-Team POTIOC

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

4 Application domains

4.1 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Entertainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4 Well-being . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5 Social and environmental responsibility

5.1 Mental Health and accessibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Augmented reality for environmental challenges
5.3 Humanitarian information visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4 Gender Equality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6 Highlights of the year

6.1 Awards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 New software, platforms, open data

7.1 New software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1.1 SHIRE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2 New platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.1 OpenVIBE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.3 Open data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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8 New results

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8.1 Practical work in quantum physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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8.2 Tangible interfaces for Railroad Traffic Monitoring . . . . . . . . . . . . . . . . . . . . . . . .
9
8.3 Avatars in Augmented Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.4 Knowledge Resources in Fabrication Workshops . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.5 Position paper: An Interdisciplinary Approach to Designing and Evaluating Data-Driven

Interactive Experiences for Sustainable Decision-Making . . . . . . . . . . . . . . . . . . . . 10

8.6 Exploring how to support Inuits in learning of RADAR imagery color scales data for sea ice

safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.7 Simulation of schizophrenia in AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
8.8 Use of Space in Immersive Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
8.9 Immersive and Collaborative Practical Activities for Education . . . . . . . . . . . . . . . . . 12
8.10 ARwavs (updated 2023)
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
8.11 Handling Non-Visible Referents in Situated Visualizations . . . . . . . . . . . . . . . . . . . . 14
8.12 Designing Resource Allocation Tools to Promote Fair Allocation: Do Visualization and

Information Framing Matter? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
8.13 Decoupling Judgment and Decision Making: A Tale of Two Tails . . . . . . . . . . . . . . . . 15
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
8.14 Zooids (book section)
8.15 Small Data – Visualizing Simple Datasets for Communication and Decision Making (HDR)
16
8.16 Impact of the baseline temporal selection on the ERD/ERS analysis for Motor Imagery-based

BCI.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

8.17 Long-term kinesthetic motor imagery practice with a BCI: Impacts on user experience,

motor cortex oscillations and BCI performances.

. . . . . . . . . . . . . . . . . . . . . . . . . 17
8.18 Detection of Motor Cerebral Activity During General Anesthesia . . . . . . . . . . . . . . . . 18

8.18.1 Detection of Motor Cerebral Activity After Median Nerve Stimulation During General

Anesthesia (STIM-MOTANA): Protocol for a Prospective Interventional Study . . . . 19

8.18.2 Detection of Cerebral Electroencephalographic Patterns After Median Nerve Stimu-
lation During Propofol-Induced General Anesthesia : a Prospective Interventional
Cohort Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

8.19 Improving motor imagery detection with a BCI based on somesthetic non invasive stimula-

tions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

8.20 DUPE MIBCI: database with user’s profile and EEG signals for motor imagery brain com-

puter interface research: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

8.21 Towards curating personalized art exhibitions in Virtual Reality with multimodal Electroencephalography-

based Brain-Computer-Interfaces: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

8.22 Independent linear discriminant analysis: The first step in including covariates in EEG

classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
8.23 Riemannian ElectroCardioGraphic signal classification . . . . . . . . . . . . . . . . . . . . . 22
8.24 Novel SPD matrix representations considering cross-frequency coupling for EEG classifica-

tion using Riemannian geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

8.25 Modeling complex EEG data distribution on the Riemannian manifold toward outlier

detection and multimodal classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

9 Bilateral contracts and grants with industry

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9.1 Bilateral contracts with industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

10 Partnerships and cooperations

10.1 International research visitors

10.1.1 Visits to international teams

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
10.2.1 Horizon Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
10.3 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

10.2 European initiatives

11 Dissemination

29
11.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
11.1.1 Scientific events: organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
11.1.2 Scientific events: selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
11.1.3 Journal
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
11.1.4 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
11.1.5 Scientific expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
11.1.6 Research administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
11.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
11.2.1 Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
11.2.2 Supervision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
11.2.3 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
11.3 Popularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
11.3.1 Articles and contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
11.3.2 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
11.3.3 Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

12 Scientific production

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12.1 Major publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
12.2 Publications of the year
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12.3 Cited publications

Project POTIOC

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Project-Team POTIOC

Creation of the Project-Team: 2014 January 01

Keywords

Computer sciences and digital sciences

A3.2.2. – Knowledge extraction, cleaning

A3.4.1. – Supervised learning

A5.1.1. – Engineering of interactive systems

A5.1.2. – Evaluation of interactive systems

A5.1.4. – Brain-computer interfaces, physiological computing

A5.1.6. – Tangible interfaces

A5.1.7. – Multimodal interfaces

A5.1.8. – 3D User Interfaces

A5.2. – Data visualization

A5.6. – Virtual reality, augmented reality

A5.6.1. – Virtual reality

A5.6.2. – Augmented reality

A5.6.3. – Avatar simulation and embodiment

A5.6.4. – Multisensory feedback and interfaces

A5.9. – Signal processing

A5.9.2. – Estimation, modeling

A9.2. – Machine learning

A9.3. – Signal analysis

Other research topics and application domains

B1.2. – Neuroscience and cognitive science

B2.1. – Well being

B2.5.1. – Sensorimotor disabilities

B2.6.1. – Brain imaging

B3.1. – Sustainable development

B3.6. – Ecology

B9.1. – Education

B9.1.1. – E-learning, MOOC

B9.5.3. – Physics

B9.6.1. – Psychology

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Inria Annual Report 2023

1 Team members, visitors, external collaborators

Research Scientists

• Martin Hachet [Team leader, INRIA, Senior Researcher, HDR]

• Pierre Dragicevic [INRIA, Researcher, HDR]

• Yvonne Jansen [CNRS, Researcher]

• Fabien Lotte [INRIA, Senior Researcher, HDR]

• Arnaud Prouzeau [INRIA, ISFP]

• Sebastien Rimbert [INRIA, ISFP]

Faculty Member

• Stephanie Cardoso [UNIV BORDEAUX MONTAI, Associate Professor Delegation, until Aug 2023]

Post-Doctoral Fellows

• Hessam Djavaherpour [UNIV BORDEAUX, Post-Doctoral Fellow]

• Claudia Krogmeier [INRIA, Post-Doctoral Fellow, from Feb 2023]

PhD Students

• Come Annicchiarico [UDL]

• Ambre Assor [INRIA]

• Vincent Casamayou [UNIV BORDEAUX]

• Edwige Chauvergne [INRIA]

• Pauline Dreyer [INRIA, from Oct 2023]

• Aymeric Ferron [INRIA, from Mar 2023]

• Morgane Koval [INRIA]

• Juliette Le Meudec [INRIA, from Oct 2023]

• Valerie Marissens [INRIA, from Dec 2023]

• Maudeline Marlier [SNCF, CIFRE]

• Leana Petiot [INRIA, from Oct 2023]

• Clara Rigaud [SORBONNE UNIVERSITE, until Jun 2023]

• Emma Tison [UNIV BORDEAUX]

• David Trocellier [UNIV BORDEAUX]

• Marc Welter [INRIA]

Technical Staff

• Axel Bouneau [INRIA, Engineer]

• Justin Dillmann [INRIA, Engineer]

• Pauline Dreyer [INRIA, Technician, until Sep 2023]

Project POTIOC

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Interns and Apprentices

• Ines Audinet [INRIA, Intern, from Nov 2023]

• Jonathan Baum [INRIA, Intern, from Mar 2023 until Aug 2023]

• Loic Bechon [INRIA, Intern, from Mar 2023 until Jun 2023]

• Emilie Clement [INRIA, Intern, from Apr 2023 until Jul 2023]

• Aymeric Ferron [INRIA, Intern, until Jan 2023]

• Juliette Le Meudec [INRIA, Intern, from Mar 2023 until Aug 2023]

• Juliette Meunier [INRIA, Intern, from May 2023 until Aug 2023]

• Leana Petiot [INRIA, Intern, from Feb 2023 until Jun 2023]

• Juliette Ribes [UNIV BORDEAUX, Intern, from Jun 2023 until Jul 2023]

• Zachary Traylor [INRIA, Intern, until Jan 2023]

Administrative Assistant

• Anne-Lise Pernel [INRIA, from Mar 2023]

2 Overall objectives

The standard human-computer interaction paradigm based on mice, keyboards, and 2D screens, has
shown undeniable benefits in a number of fields. It perfectly matches the requirements of a wide
number of interactive applications including text editing, web browsing, or professional 3D modeling.
At the same time, this paradigm shows its limits in numerous situations. This is for example the case in
the following activities: i) active learning educational approaches that require numerous physical and
social interactions, ii) artistic performances where both a high degree of expressivity and a high level of
immersion are expected, and iii) accessible applications targeted at users with special needs including
people with sensori-motor and/or cognitive disabilities.

To overcome these limitations, Potioc investigates new forms of interaction that aim at pushing the
frontiers of the current interactive systems. In particular, we are interested in approaches where we vary
the level of materiality (i.e., with or without physical reality), both in the output and the input spaces. On
the output side, we explore mixed-reality environments, from fully virtual environments to very physical
ones, or between both using hybrid spaces. Similarly, on the input side, we study approaches going from
brain activities, that require no physical actions of the user, to tangible interactions, which emphasize
physical engagement. By varying the level of materiality, we adapt the interaction to the needs of the
targeted users.

The main applicative domains targeted by Potioc are Education, Art, Entertainment and Well-being.
For these domains, we design, develop, and evaluate new approaches that are mainly dedicated to
non-expert users. In this context, we thus emphasize approaches that stimulate curiosity, engagement,
and pleasure of use.

3 Research program

To achieve our overall objective, we follow two main research axes, plus one transverse axis, as illustrated
in Figure 2.

In the first axis dedicated to Interaction in Mixed-Reality spaces, we explore interaction paradigms
that encompass virtual and/or physical objects. We are notably interested in hybrid environments that
co-locate virtual and physical spaces, and we also explore approaches that allow one to move from one
space to the other.

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Inria Annual Report 2023

Figure 1: Tobe combines tangible interaction, spatial augmented reality, and physiological computing. It
allows users to feel and explore their inner states.

The second axis is dedicated to Brain-Computer Interfaces (BCI), i.e., systems enabling user to
interact by means of brain activity only. We target BCI systems that are reliable and accessible to a large
number of people. To do so, we work on brain signal processing algorithms as well as on understanding
and improving the way we train our users to control these BCIs.

Finally, in the transverse axis, we explore new approaches that involve both mixed-reality and neuro-
physiological signals. In particular, tangible and augmented objects allow us to explore interactive
physical visualizations of human inner states. Physiological signals also enable us to better assess user
interaction, and consequently, to refine the proposed interaction techniques and metaphors.

Figure 2: Main research axes of Potioc.

From a methodological point of view, for these three axes, we work at three different interconnected
levels. The first level is centered on the human sensori-motor and cognitive abilities, as well as user
strategies and preferences, for completing interaction tasks. We target, in a fundamental way, a better
understanding of humans interacting with interactive systems. The second level is about the creation of
interactive systems. This notably includes development of hardware and software components that will
allow us to explore new input and output modalities, and to propose adapted interaction techniques.
Finally, in a last higher level, we are interested in specific application domains. We want to contribute to
the emergence of new applications and usages, with a societal impact.

Project POTIOC

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4 Application domains

4.1 Education

Education is at the core of the motivations of the Potioc group. Indeed, we are convinced that the
approaches we investigate—which target motivation, curiosity, pleasure of use and high level of inter-
activity—may serve education purposes. To this end, we collaborate with experts in Educational Sciences
and teachers for exploring new interactive systems that enhance learning processes. We are currently
investigating the fields of astronomy, optics, and neurosciences. We have also worked with special
education centres for the blind on accessible augmented reality prototypes. Currently, we collaborate
with teachers to enhance collaborative work for K-12 pupils. In the future, we will continue exploring
new interactive approaches dedicated to education, in various fields. Popularization of Science is also a
key domain for Potioc. Focusing on this subject allows us to get inspiration for the development of new
interactive approaches.

4.2 Art

Art, which is strongly linked with emotions and user experiences, is also a target area for Potioc. We
believe that the work conducted in Potioc may be beneficial for creation from the artist point of view,
and it may open new interactive experiences from the audience point of view. As an example, we have
worked with colleagues who are specialists in digital music, and with musicians. We have also worked
with jugglers and we are currently working with a scenographer with the goal of enhancing interactivity
of physical mockups and improve user experience.

4.3 Entertainment

Similarly, entertainment is a domain where our work may have an impact. We notably explored BCI-based
gaming and non-medical applications of BCI, as well as mobile Augmented Reality games. Once again,
we believe that our approaches that merge the physical and the virtual world may enhance the user
experience. Exploring such a domain will raise numerous scientific and technological questions.

4.4 Well-being

Finally, well-being is a domain where the work of Potioc can have an impact. We have notably shown
that spatial augmented reality and tangible interaction may favor mindfulness activities, which have
been shown to be beneficial for well-being. More generally, we explore introspectibles objects, which are
tangible and augmented objects that are connected to physiological signals and that foster introspection.
We explore these directions for general public, including people with special needs.

5 Social and environmental responsibility

5.1 Mental Health and accessibility

In collaboration with colleagues in neuropsychology (Antoinette Prouteau), we are exploring how aug-
mented reality can help to better explain schizophrenia and fight against stigmatization. This project is
directly linked to Emma Tison’s PhD thesis and our Inria ”Action exploratoire” LiveIt.

Previously, we have been interested in designing and developing tools that can be used by people
suffering from physiological or cognitive disorders. In particular, we used the PapARt tool developed
in the team to contribute making board games accessible for people suffering from visual impairment
[58]. We also designed a MOOC player, called AIANA, in order to ease the access of people with cognitive
disorders (attention, memory). See the dedicated page.

As part of our research on Brain-Computer Interfaces, we also worked with users with severe motor
impairment (notably tetraplegic users or stroke patients) to restore or replace some of their lost functions,
by designing BCI-based assistive technologies or motor rehabilitation approaches, see, e.g., [1].

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Inria Annual Report 2023

5.2 Augmented reality for environmental challenges

In response to the big challenge of climate change, we are currently orienting our research towards
approaches that may contribute to pro-environmental behaviors. To do so, we are framing research
directions and building projects with the objective of putting our expertise in HCI, visualization, and
mixed-reality to work for the reduction of human impact on the planet (see [45]). In 2023, we officially
started the ANR Be·aware project dedicated to this subject with colleagues in environmental sciences
(CIRED) and behavioral sciences (Lessac). See also ARwavs in 8.10.

5.3 Humanitarian information visualization

Members of the team are involved in research promoting humanitarian goals, such as studying how
to design visualizations of humanitarian data in a way that promotes charitable donations to traveling
migrants and other populations in need, or how to convey income inequalities in a way that makes people
more likely to favor redistribution. Some of this research has been featured in a recent HDR dissertation
(see Section 8.15), but more research is underway.

5.4 Gender Equality

Members of the team are involved in research on gender in academia, such as patterns of collaboration
between men and women, and gender balance in organization and steering committees, and among
award recipients (more in the 2022 RADAR report).

6 Highlights of the year

• Pierre Dragicevic defended his HDR.

• ERC “Proof of concept” grant SPEARS (Skill Performance Estimation from cARdiac Signals) accepted

6.1 Awards

• Yvonne Jansen received the bronze medal of CNRS.

• Fabien Lotte received the Nature Mentorship Award 2023 (“Mid-career” category)

• Fabien Lotte received the Lovelace-Babbage Award 2023 from the French academy of science in

collaboration with the French Informatics Society

7 New software, platforms, open data

7.1 New software

7.1.1 SHIRE

Name: Simulation of Hobit for an Interactive and Remote Experience

Keywords: Unity 3D, Optics, Education

Functional Description: SHIRE allows to have a simulation of the HOBIT device, an augmented table
enhancing the teaching of optics at university level, in a completely digital version. It can be used
outside of the classroom and still provide an experience similar to the one available on HOBIT.
SHIRE can be used in a collaborative way, thanks to the connectivity between several instances of
the software, allowing to work in groups on the same session.

Contact: Vincent Casamayou

Participants: Vincent Casamayou, Justin Dillmann, Martin Hachet, Bruno Bousquet, Lionel Canioni

Project POTIOC

7.2 New platforms

7.2.1 OpenVIBE

Participants:

Axel Bouneau, Fabien Lotte.

7

External collaborators:

Thomas Prampart (Inria Rennes - Hybrid), Anatole Lécuyer (Inria
Rennes - Hybrid).

OpenViBE is an open-source and free software dedicated to designing, testing and using brain-
computer interfaces. In 2023, version 3.5.0 of OpenViBE was released, and some developpement has
been made towards the upcomming 3.6.0 release. These updates include, among others, the following
features that were developped by the Potioc team.

OpenViBE designer:

• New metaboxes: tonic and phasic filters for Galvanic Skin Response (GSR) (3.6.0)

• New metabox: asymmetry index for Electroencephalography (EEG) (3.6.0)

• New box: pulse rate calculator for Photoplethysmography (PPG) (3.6.0)

• Various bug fixes (3.5.0) and (3.6.0)

OpenViBE Acquisition server:

• Updated driver: Shimmer GSR driver (preformance and user interface improvements) (3.5.0)

Figure 3: The shimmer GSR+ device being used with OpenViBE

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7.3 Open data

Inria Annual Report 2023

• osf.io/nu4z3/ – Research material and particpants’ sketches shared on OSF for the VIS’23 short

paper Towards Autocomplete Strategies for Visualization Construction [40]

• osf.io/q5fr6/ – Fabrication instructions for the prototype generated for the project Edo: A Particip-

atory Data Physicalization on the Climate Impact of Dietary Choices[38]

• osf.io/ufzp5/ – Research material (including data and analysis scripts) and Preregistration shared

on OSF for the paper Decoupling Judgment and Decision Making: A Tail of Two Tails [20].

• osf.io/v4yxs/ – Research material (including data and analysis scripts) and Preregistration shared

on OSF for the paper Augmented Reality waste accumulation visualization evaluation [45].

• zenodo.org/records/7554429 – A large public EEG database with users’ profile information for

motor imagery Brain-Computer Interface research [49]

8 New results

8.1 Practical work in quantum physics

Participants:

Vincent Casamayou, Justin Dillmann, Martin Hachet.

External collaborators: Bruno Bousquet (Univ. Bordeaux), Lionel Canioni (Univ. Bordeaux),

Jean-Paul Guillet (Univ. Bordeaux).

HQBIT (Hybrid Quantum Bench for Innovative Teaching), is a tangible and AR optical bench that
we are developing to perform quantum optics experiments, based on the HOBIT platform. It allows the
user to reproduce quantum optics experiments in a real-time simulated environment, using tangible
reproductions of optical elements, and augmented reality to provide pedagogical information. This
simulation includes numerous optical components (detectors, nonlinear crystal, pulsed laser and so
on) and light characteristics (e.g. photons statistics and entanglement), which are required to recreate
quantum optics phenomenons. This system was designed directly in collaboration with physicians
working in the optics field to ensure the precision and accuracy of the simulation. Using HQBIT students
can reproduce from scratch, key quantum optics experiments such as Alain Aspect’s experiment, that
demonstrate the entanglement between a pair of photons, or the Mach-Zehnder Interferometer, that
illustrate wave-particle duality. See 4 and [48].

8.2 Tangible interfaces for Railroad Traffic Monitoring

Participants: Maudeline Marlier, Arnaud Prouzeau, Martin Hachet.

Maudeline Marlier started her PhD in March 2022 at Potioc on a Cifre contract with the SNCF on the
use of tangible interaction in railroad traffic monitoring control rooms. Automation in such context is
increasing, particularly with the expanding train traffic worldwide, the role of humans remains essential.
This is particularly true in case of crisis, where operators with different expertise need to collaborate
to make critical decisions. We conducted an in-the-field study to observe how operators work and
collaborate, especially in crisis scenarios, and identify the limits of the current approaches. Inspired by
this, we developed a prototype to investigate the use of actuated tangible tokens on a tabletop to visualise
and collaboratively explore different solutions to resolve incidents (see Fig. 5). To gauge the implications

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Figure 4: TPhotons (light particles) detection experiment on HQBIT. On the projection screen, the user
can directly compare the arrivals of photons on both Detectors. This experiment illustrates the wave-
particle duality principle

and opportunities of our approach we performed formative evaluations with operators in a high-speed
train control centre. Our results suggest that actuated tangible tokens are promising for collaboration,
allowing the addition of information with a simple gesture and understanding easily through movements
on the table. A paper on this is going to be submitted at ACM ISS 2024.

Figure 5: Schema (left) and picture (right) of the implemented prototype with projection and actuated
tangible tokens.

8.3 Avatars in Augmented Reality

Participants:

Adélaïde Genay, Martin Hachet.

External collaborators:

Anatole Lécuyer (Inria Rennes - Hybrid), Kiyoshi Kiyokawa (NAIST,
Japan), Riku Otono (NAIST, Japan).

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Inria Annual Report 2023

In 2023, we have continued our work with our colleagues from Japan, how it is possible to enhance the
Sense of Embodiment (SoE) by introducing transitions between one real body and its virtual counterpart.
In particular, we have showed that visual transitions effectively improve the SoE [32]. We are also exploring
priming approaches that tend to show that SoE can be enhanced when the subject follows a mental
preparation protocol.

8.4 Knowledge Resources in Fabrication Workshops

Participants: Clara Rigaud, Yvonne Jansen.

External collaborators: Gilles Bailly.

Creating, using, and sharing knowledge resources is central to the culture and practice of fabrication
workshops. We reviewed the research literature on these knowledge resources including the fields of
Human Computer Interaction, but also Education and Design. We identify four goals that a maker may
pursue when creating a resource: (1) Representing a fabrication project, (2) Reusing one’s work, (3)
Supporting reflection et (4) Communicating. For each of these goals, we articulate two challenges that
makers may face. We then illustrate, through four examples, how this set of challenges can be used as a
grid to compare different approaches, before discussing the relationship between the challenges and the
tools to address them. This work resulted in an article published at IHM [36].

8.5 Position paper: An Interdisciplinary Approach to Designing and Evaluating

Data-Driven Interactive Experiences for Sustainable Decision-Making

Participants:

Yvonne Jansen, Ambre Assor, Pierre Dragicevic, Aymeric Ferron,
Arnaud Prouzeau, Martin Hachet.

External collaborators:

Thomas Le Gallic (CIRED), Ivan Ajdukovic (LESSAC), Eleonora Montag-
ner (LESSAC), Eli Spiegelman (LESSAC), Angela Sutan (LESSAC)
.

We wrote a position paper on our interdisciplinary research approach taken in the ANR Be·Aware
project: Running long-term field studies is a valuable yet slow and costly approach to test the efficacy
of interaction designs on people’s everyday decision making and behavior. In this position paper we
described the rationale behind an interdisciplinary approach to designing and evaluating data-driven in-
teractive experiences for sustainable decision-making. We are a group consisting of HCI and visualization
researchers, energy-economy modeling experts who work on mitigation pathways, and behavioral eco-
nomists who run controlled experiments to study how people make decisions in an incentivized context.
The intent of this collaboration is twofold: (1) we study how to design efficient data-driven experiences to
help people build an intuition concerning the sustainability of daily choices and actions; (2) we explore
the mutual benefit of working across disciplinary boundaries to go beyond the limits of our respective
methodological toolboxes. We illustrated our approach through an example of a work-in-progress.

8.6 Exploring how to support Inuits in learning of RADAR imagery color scales data

for sea ice safety

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Participants: Hessam Djavaherpour, Yvonne Jansen.

External collaborators:

Lynn Moorman (Mount Royal University), Faramarz Samavati (Univer-
sity of Calgary).

The changing climate and increasingly unpredictable sea ice conditions have created life-threatening
risks for Inuit, the residents of the Arctic, who depend on the ice for transportation and livelihood. In
response, they are turning to technology (e.g., RADAR imagery from the Canadian RADARSAT satellite) to
augment their traditional knowledge of the ice and to map potential hazards. The difficulty lies in the
actual RADAR interpretation process. In order to support understanding of the RADAR image content,
we reported a work-in-progress, INTUIT, a physicalization that represents the RADAR reflection strength,
which is highly influenced by surface roughness, as a tactile texture. Such tactile texture is made by
resampling the RADAR imagery to a number of UV cells and mapping the average brightness value of
each cell to a physical variable. A proof of concept was designed for a region in Baffin Island (Nunavut)
and sent to the Arctic for initial feedback. Preliminary study results were promising and suggest that
INTUIT could facilitate the interpretation learning process for RADAR imagery.

8.7 Simulation of schizophrenia in AR

Participants: Claudia Krogmeier, Emma Tison, Justin Dillmann, Arnaud Prouzeau,

Martin Hachet.

External collaborators:

Antoinette Prouteau (Université de Bordeaux).

In collaboration with colleagues in neurophysiology from Université of Bordeaux, we explore the use
of AR to let students in mental health better understand what schizophrenia is. This work is part of the
Inria ”Action Exploratoire” LiveIt and benefit from and interdisciplinary PhD funding from Univeersité of
Bordeaux.

Symptoms of schizophrenia are often difficult for those without schizophrenia to understand, which
can lead to significant stigmatization towards those who experience this disorder. There exist numerous
simulations of schizophrenia across different modalities such as audio recordings, desktop simulations,
as well as virtual and augmented reality simulations which have tried to mitigate stigma. While many
of these simulations have proven efficacious in reducing multiple elements of stigma, several others
have instead increased the desire for social distance from those with schizophrenia. In our work, we are
designing an interactive simulation of schizophrenia within an augmented reality application. We will
investigate how users experience various symptoms, and determine if the developed simulation reduces
stigma towards those with schizophrenia. We will collect both qualitative and quantitative data in order
to understand the user’s experience with the simulation, and expand upon our prototype in the future in
order to investigate the representation of additional symptomatology through augmented reality.

8.8 Use of Space in Immersive Analytics

Participants:

Arnaud Prouzeau, Edwige Chauvergne, Pierre Dragicevic, Mar-
tin Hachet.

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Inria Annual Report 2023

External collaborators:

Yidan Zhang (Monash University), Barrett Ens (Monash University),
Sarah Goodwin (Monash University), Kadek Satriadi (Monash Univer-
sity).

An immersive system is one whose technology allows us to “step through the glass” of a computer
display to engage in a visceral experience of interaction with digitally-created elements. As immersive
technologies have rapidly matured to bring commercially successful virtual and augmented reality
(VR/AR) devices and mass market applications, researchers have sought to leverage its benefits, such
as enhanced sensory perception and embodied interaction, to aid human data understanding and
sensemaking. In 2023, we focused mainly on the immersive visualisation of spatio-temporal datasets and
on storytelling.

We particularly focused on space-time cube visualisation. The space-time cube is a common approach
for spatial-temporal data visualisation. However, little research has investigated its design choices in
virtual environments. We conducted two user studies to explore the relative effectiveness of visual
encodings for an immersive layered space-time cube. In the first study, we evaluated data encodings on
different map scales (See Fig. 6). Participants performed value identification, value comparison, and
trend identification tasks. In the second study, we investigated the effect of shapes of visual objects on
the perception of encoding for comparison and trend tasks. Our results suggested that colour overall
performs the best while the effectiveness of area and thickness varies for different map scales and task
types. The impact of shape is limited, as the results show that colour is more effective than area across the
majority of studied shapes. We believe the findings will guide future designs of virtual space-time cube
visualisations in enhancing data understanding. This work is under review at the conference CHI 2024.

Figure 6: llustration of the immersive space-time cube prototype used in Study 1. A campus map showing
one year’s worth of monthly energy consumption data for the selected building. The study tested the
accuracy, speed and user preference of three popular data encodings (colour, area, thickness) across
three map scales (small, medium, large) and for three types of user task (identify, compare and trend).
Left: colour encoding on small scale. Middle: area encoding on medium scale. Right: thickness encoding
on large scale.

With the PhD student Edwige Chauvergne, we also started exploring the use of immersive technologies
to visualise data in the context of storytelling. More specifically we are studying the transition between
abstract visualisation with quantitative information with an exocentric view and the context of one
specific data point with an egocentric point of view that can be more engaging, visceral and lead to an
enhanced emotional response. We used data on feminicides in France as a case study.

8.9 Immersive and Collaborative Practical Activities for Education

Participants:

Juliette Le Meudec, Arnaud Prouzeau, Martin Hachet.

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Figure 7: Creative problem-solving task implemented to study collaboration. The participants have to
design a vehicules using four different cubes.

External collaborators:

Anastasia Bezerianos (Equipe ILDa - Inria Saclay), Chloé Mer-
cier (Equipe Mnemosyne - Inria Bordeaux).

Immersive technologies hold significant promise in engaging students in educational activities.
Theses technologies can foster interaction, immersion, and collaboration among students, creating
unique opportunities to enhance various aspects of learning. However, collaboration in virtual reality
can be challenging. Habits of collaboration developed in real life may not necessarily translate to this
environment. For instance, some communication and problem-solving methods may require some
adaptation as there is a lack of some "social clues" in VR such as the absence of facial expressions, giving
rise to challenges associated with the use of these emerging educational technologies. In addition, VR
also offers highly interesting new perspectives for education, enabling us to imagine new ways of working
together. Therefore, it becomes imperative to closely explore the process of collaboration in virtual reality,
with a focus on the learning perspective, an area where virtual reality is experiencing significant growth.
We thus implemented a virtual reality application specifically designed to study collaboration between
two individuals engaged in an educational task focused on creative problem-solving. This task was in-
spired by a task designed in the ANR project CreaCube () with real physical robots. In this task, participants
are asked to assemble a vehicle with 4 cubes provided without any explanations about the functionality
of each cube (see Fig. 7). They have to observe the cubes and trial different combinations to allow them
understand what each cube do. Our application offers a unique way of studying collaborative processes
in the specific context of learning, opening up new avenues for improving educational experiences using
virtual reality. This is part of the ANR JCJC project ICARE and is going to be submitted as a Work In
Progress at IHM 2024.

8.10 ARwavs (updated 2023)

Participants:

Ambre Assor, Pierre Dragicevic, Arnaud Prouzeau, Martin Hachet.

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Inria Annual Report 2023

Figure 8: Examples of augmented reality visualization experiences. Single-use plastic cups accumulated
for a given period of time (left); Material displaced and emitted to manufacture about eight smartphones
(middle); Volume of dirty water produced, visualized in a bathroom as if it was flooded (right).

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 (see Figure 8) 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.

Late 2022, we published an early preprint on this work [45]. In 2023, we published the work in the ACM
Journal on Computing and Sustainable Societies (in press) and gave a demo at the CHI 2023 conference
[25].

8.11 Handling Non-Visible Referents in Situated Visualizations

Participants:

Ambre Assor, Arnaud Prouzeau, Martin Hachet, Pierre Dragicevic.

Situated visualizations are a type of visualization where data is presented next to its physical referent
(i.e., the physical object, space, or person it refers to), often using augmented-reality displays. While
situated visualizations can be beneficial in various contexts and have received research attention, they are
typically designed with the assumption that the physical referent is visible. However, in practice, a physical
referent may be obscured by another object, such as a wall, or may be outside the user’s visual field. In a
paper published in the Transactions on Visualization & Computer Graphics (TVCG) [16], we proposed
a conceptual framework and a design space to help researchers and user interface designers handle
non-visible referents in situated visualizations. We first provided an overview of techniques proposed
in the past for dealing with non-visible objects in the areas of 3D user interfaces, 3D visualization, and
mixed reality. From this overview, we derived a design space that applies to situated visualizations and
employ it to examine various trade-offs, challenges, and opportunities for future research in this area.

8.12 Designing Resource Allocation Tools to Promote Fair Allocation: Do Visualiza-

tion and Information Framing Matter?

Participants:

Pierre Dragicevic.

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External collaborators:

Arnav Verma, Luiz Morais, Fanny Chevalier.

Studies on human decision-making focused on humanitarian aid have found that cognitive biases
can hinder the fair allocation of resources. However, few HCI and Information Visualization studies have
explored ways to overcome those cognitive biases. This work published at the CHI 2023 Conference
on Human Factors in Computing Systems [39] investigates whether the design of interactive resource
allocation tools can help to promote allocation fairness. We specifically studied the effect of presentation
format (using text or visualization) and a specific framing strategy (showing resources allocated to groups
or individuals). In our three crowdsourced experiments, we provided different tool designs to split money
between two fictional programs that benefit two distinct communities. Our main finding indicated that
individual-framed visualizations and text may be able to curb unfair allocations caused by group-framed
designs. This work opens new perspectives that can motivate research on how interactive tools and
visualizations can be engineered to combat cognitive biases that lead to inequitable decisions.

8.13 Decoupling Judgment and Decision Making: A Tale of Two Tails

Participants:

Pierre Dragicevic.

External collaborators:

Ba¸sak Oral, Alexandru Telea, Evanthia Dimara.

Is it true that if citizens understand hurricane probabilities, they will make more rational decisions for
evacuation? Finding answers to such questions is not straightforward in the literature because the terms
“judgment” and “decision making” are often used interchangeably. This terminology conflation leads
to a lack of clarity on whether people make suboptimal decisions because of inaccurate judgments of
information conveyed in visualizations or because they use alternative yet currently unknown heuristics.
To decouple judgment from decision making, we reviewed relevant concepts from the literature and
presented two preregistered experiments (N=601) to investigate if the task (judgment vs. decision making),
the scenario (sports vs. humanitarian), and the visualization (quantile dotplots, density plots, probability
bars) affect accuracy. While experiment 1 was inconclusive, we found evidence for a difference in
experiment 2. Contrary to our expectations and previous research, which found decisions less accurate
than their direct-equivalent judgments, our results pointed in the opposite direction. Our findings
further revealed that decisions were less vulnerable to status-quo bias, suggesting decision makers may
disfavor responses associated with inaction. We also found that both scenario and visualization types
can influence people’s judgments and decisions. Although effect sizes are not large and results should
be interpreted carefully, we concluded that judgments cannot be safely used as proxy tasks for decision
making, and discuss implications for visualization research and beyond. This work was published in
the IEEE Transactions on Visualization and Computer Graphics [20]. Materials and preregistrations are
available at osf.io/ufzp5/.

8.14 Zooids (book section)

Participants:

Pierre Dragicevic.

External collaborators: Mathieu Le Goc, Charles Perin, Sean Follmer, Jean-Daniel Fekete.

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Physical data visualizations tap into our lifelong experience of perceiving and manipulating the
physical world, either alone or with other people. However, most physical visualizations are either
monolithic and static, or require human intervention to be rearranged. Back in 2018, we drew inspiration
from existing physical interactive systems and data storytelling practices with physical tokens to develop
Zooids, tiny wheeled robots that can move rapidly on any horizontal surface. We used Zooids to explore
physical data visualizations that can (1) be manipulated by humans, and (2) update themselves through
computerized mechanisms. In 2023, we wrote a section [43] in the book Making with Data: Physical
Design and Craft in a Data-Driven World to explain our design process.

8.15 Small Data – Visualizing Simple Datasets for Communication and Decision

Making (HDR)

Participants:

Pierre Dragicevic.

In 2023, Pierre Dragicevic defended his habilitation thesis [44]. This habilitation thesis presents
research projects that explore how data visualizations can be used to communicate quantitative facts and
support decisions. The thesis identifies the umbrella topic of “small data” as the common denominator for
these projects, as they all involve datasets that are smaller than what is typically found in the information
visualization literature. Although much of this literature focuses on large datasets, this thesis shows that
we often do not know how to best visualize even small datasets, and that interesting research questions
can also arise from such datasets.

The first part of this thesis focuses on supporting rational judgments and decisions with data visualiz-
ations. It examines whether data visualization can improve reasoning with base rates, it looks at whether
a cognitive bias called the attraction effect transfers to data visualizations, and discusses how to generally
evaluate data visualizations for decision making.

The second part of this thesis discusses how to support effective communication with data visualiz-
ations. It begins by exploring different ways in which researchers can communicate their data to their
peers: first through tabular visualizations, and then through multiverse analyses. It then reports on two
studies examining how to communicate data to large audiences: a replication study on whether trivial
charts can hinder truthful communication, and a study on how to convey data on humanitarian issues.
Finally, a concluding chapter brings together several of the research problems discussed here by
offering perspectives on how data visualization can support rational decisionmaking and effective com-
munication on humanitarian issues. It discusses how can the effective altruism movement inform
research in this area, and how may immersive displays be used to connect people to invisible or distant
suffering.

8.16 Impact of the baseline temporal selection on the ERD/ERS analysis for Motor

Imagery-based BCI.

Participants:

Sébastien Rimbert, David Trocellier, Fabien Lotte.

Motor Imagery-based Brain-Computer Interfaces (MI-BCIs) are neurotechnologies that exploit the
modulation of sensorimotor rhythms over the motor cortices, respectively known as Event-Related
Desynchronization (ERD) and Synchronization (ERS). The interpretation of ERD/ERS is directly related
to the selection of the baseline used to estimate them, and might result in a misleading ERD/ERS
visualization. In fact, in BCI paradigms, if two trials are separated by a few seconds, taking a baseline
close to the end of the previous trial could result in an over-estimation of the ERD, while taking a baseline
too close to the upcoming trial could result in an underestimation of the ERD. This phenomenon may
cause a functional misinterpretation of the ERD/ERS phenomena in MI-BCI studies. This may also impair
BCI performances for MI vs Rest classification, since such baselines are often used as resting states. In
this paper, we propose to investigate the effect of several baseline time window selections on ERD/ERS

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modulations and BCI performances. Our results show that considering the selected temporal baseline
effect is essential to analyze the modulations of ERD/ERS during MI-BCI use [37].

Figure 9: Topographic map of ERD/ERS% (grand average, n=71) in the alpha/mu+beta band during the
right-hand and left-hand MIs for both calibration and user training sessions for different baselines. A blue
colour corresponds to a strong ERD and a red one to a strong ERS. Red electrodes indicate a significant
difference (p<0.01) with a FDR (False Discovery Rate) correction.

8.17 Long-term kinesthetic motor imagery practice with a BCI: Impacts on user

experience, motor cortex oscillations and BCI performances.

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Inria Annual Report 2023

Participants:

Sébastien Rimbert.

External collaborators:

Stéphanie Fleck (Univ. Lorraine).

Kinesthetic motor imagery (KMI) generates specific brain patterns in sensorimotor rhythm over the
motor cortex (called event-related (de)-synchronization, ERD/ERS), allowing KMI to be detected by a
Brain-Computer Interface (BCI) through electroencephalographic (EEG) signal. Because performing a
KMI task stimulates synaptic plasticity, KMI-based BCIs hold promise for many applications requiring
long-term KMI practice (e.g., sports training or post-stroke rehabilitation). However, there is a lack of
studies on the long-term KMI-based BCI interactions, especially regarding the relationship between
intrapersonal factors and motor pattern variations. This pilot study aims to understand better (i) how
brain motor patterns change over time for a given individual, (ii) whether intrapersonal factors might
influence BCI practice, and (iii) how the brain motor patterns underlying the KMI task (i.e., ERDs and
ERSs) are modulated over time by the BCI user’s experience. To this end, we recruited an expert in
this mental task who performed over 2080 KMIs in 26 different sessions over a period of five months.
The originality of this study lies in the detailed examination of cross-referenced data from EEG signals,
BCI data performance, and 13 different surveys. The results show that this repetitive and prolonged
practice did not diminish his well-being and, in particular, generated a sense of automatization of the
task. We observed a progressive attenuation of the ERD amplitude and a concentration in the motor
areas as the sessions accumulated. All these elements point to a phenomenon of neural efficiency. If
confirmed by other studies, this phenomenon could call into question the quality of the BCI in providing
continuous stimulation to the user. In addition, the results of this pilot study provide insights into what
might influence the response of the motor cortex (e.g. emotions, task control, diet, etc.) and promising
opportunities for improving the instructional design of BCIs intended for long-term use [21].

Figure 10: Diagram describing the BCI performance of accuracy (TS+LR method) and the feeling of the
KMI task proficiency and of being faced with a challenge for all sessions.

8.18 Detection of Motor Cerebral Activity During General Anesthesia

Participants:

Sebastien Rimbert, Fabien Lotte, Valérie Marissens.

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External collaborators: Claude Mestelman (CHRU Brabois), Laurent Bougrain (Univ. Lor-
raine), Denis Schmartz (Erasme Hospital), Ana Maria Cebolla (Univ.
Bruxelles), Guy Cheron (Univ. Bruxelles), Seyed Javad Bidgoli (CHRU
Brugmann).

8.18.1 Detection of Motor Cerebral Activity After Median Nerve Stimulation During General Anes-

thesia (STIM-MOTANA): Protocol for a Prospective Interventional Study

Background Accidental awareness during general anesthesia (AAGA) is defined as an unexpected aware-
ness of the patient during general anesthesia. This phenomenon occurs in 1%-2% of high-risk practice
patients and can cause physical suffering and psychological after-effects, called posttraumatic stress
disorder. In fact, no monitoring techniques are satisfactory enough to effectively prevent AAGA; therefore,
new alternatives are needed. Because the first reflex for a patient during an AAGA is to move, but cannot
do so because of the neuromuscular blockers, we believe that it is possible to design a brain-computer
interface (BCI) based on the detection of movement intention to warn the anesthetist. To do this, we pro-
pose to describe and detect the changes in terms of motor cortex oscillations during general anesthesia
with propofol, while a median nerve stimulation is performed. We believe that our results could enable
the design of a BCI based on median nerve stimulation, which could prevent AAGA. Objective To our
knowledge, no published studies have investigated the detection of electroencephalographic (EEG) pat-
terns in relation to peripheral nerve stimulation over the sensorimotor cortex during general anesthesia.
The main objective of this study is to describe the changes in terms of event-related desynchronization
and event-related synchronization modulations, in the EEG signal over the motor cortex during general
anesthesia with propofol while a median nerve stimulation is performed [22].

8.18.2 Detection of Cerebral Electroencephalographic Patterns After Median Nerve Stimulation

During Propofol-Induced General Anesthesia : a Prospective Interventional Cohort Study

Devices used to assess depth of anesthesia and clinical parameters may not be sufficient to prevent
intraoperative accidental awareness. An alternative would be to detect the patient’s intention to move in
order to alert the medical staff. We believe that the data obtained after multiple median nerve stimulation
(MNS) during general anesthesia will help us to prevent intraoperative awareness. In this prospective,
interventional trial, 30 volunteers aged from 18 to 81 years with informed consent will be enrolled
for scheduled surgery from 15th January 2023 to 31st December 2026. This study is approved by the
CHU Brugmann ethical committee (CE 2021/225) and is registered at EUDRACT (2021-006457-56) and
ClinicalTrials.gov (NCT05272202). EEG data based on MNS is first recorded with the patient awake, then
a second recording is made under general anesthesia during the surgery. MNS is obtained by electrodes
placed on the wrist. Our intermediate results (n=4 curarized patients) shows the ERS in the mu/beta
frequency band after MNS before general anesthesia. After propofol induction, the post-stimulation ERS
disappears significantly. The preliminary data extracted from the ERD/ERS consecutive to MNS seems to
disappear with high concentration of propofol contrary to previous studies at lower levels2. Therefore,
this study is not conclusive in terms of the ERD/ERS patterns used but other EEG features (i.e., brain
connectivity, somatosensory evoked potential) could be investigated and will be the subject of future
research [52].

8.19 Improving motor imagery detection with a BCI based on somesthetic non

invasive stimulations

Participants:

Sebastien Rimbert.

One of the most prominent BCI types of interaction is Motor Imagery (MI)-based BCI. Users control a
system by performing MI tasks, e.g., imagining hand/foot movements detected from EEG signals. Indeed,
movements and imagination of movements activate similar neural networks, enabling the MI-based

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BCI to exploit the modulations known as Event-Related Desynchronization (ERD) and Event-Related
Synchronization (ERS). However, two important challenges remain before using such MI-BCIs on a large
scale: (i) be able to detect the MI of the user without any temporal markers for instructions (often given by
sound or visual cues) and (ii) achieve sufficient accuracy (>80%) to ensure the reliability of a BCI device
that could be used by the participants. We presented this work at the BCI meeting 2023 [51].

8.20 DUPE MIBCI: database with user’s profile and EEG signals for motor imagery

brain computer interface research:

Participants:

Pauline Dreyer, Aline Roc, Camille Benaroch, Thibaut Monseigne,
Sebastien Rimbert, Fabien Lotte.

The creation of the large BCI database published on Zenodo on January 9, 2023, containing (elec-
troencephalographic signals from 87 human participants, associated BCI user performances, detailed
information on demographics, personality profile, cognitive traits, and experimental instructions and
codes) led to an article [19] published in Scientific Data by Nature on September 5, 2023. It presents
the database and explains 1) the experimental protocols, 2) the usefulness of the database for different
studies, 3) and the technical validation of the database. Indeed, our results show consistency with the
literature, both in terms of classification performance for right-left discrimination (see Fig. 11) and in
terms of ERSP variation. During the motor imagery tasks, there is an activation of the motor cortex with
contralateral ERD (see Fig. 12).

Figure 11: Scatter plot showing the average BCI performance of the 4 runs per subject. Blue points
represent BCI performance averaged over the 4 recorded per participant. Connected black lines indicate
the standard deviation per run. Individual chance level: 58,7%, Median: 57,5%, Database chance level:
51%.

Such database could prove useful for various studies, including but not limited to: (1) studying the
relationships between BCI users’ profiles and their BCI performances, (2) studying how EEG signals
properties varies for different users’ profiles and MI tasks, (3) using the large number of participants to
design cross-user BCI machine learning algorithms or (4) incorporating users’ profile information into
the design of EEG signal classification algorithms.

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Figure 12: Topographic maps illustrating the ERD/ERS% (grand mean, n=80) in the alpha/mu+beta band
during both right and left motor imagery (MI) tasks in both the calibration and user training phases. The
time window considered is from 3 to 8 seconds.

8.21 Towards curating personalized art exhibitions in Virtual Reality with mul-

timodal Electroencephalography-based Brain-Computer-Interfaces:

Participants: Marc Welter, Axel Bouneau, Jonathan Baum, Ines Audinet, Fa-

bien Lotte.

The EEG correlates of art preference are not yet well understood scientifically. We contributed a
literature review on the oscillatory EEG correlates of art preference that was presented during as posters
at the BCI Society Meeting and in Torun, and submitted for publication in the journal Frontiers in
Neuroergonomics. We also developed a novel experimental protocol to measure a subject’s aesthetic
experience in a virtual museum environment with EEG, GSR and PPG. To this end, we also established a
data set of diverse visual art works that will be released in the public domain. This work was presented as
a talk at CORTICO2023 and at the BCI Society Meeting 2023 in a masterclass [56]. We, then, collected
physiological data and subjective preference ratings from 20 healthy adult subjects. Preliminary data
analysis suggests that, at least for some persons, preference for static visual art correlates positively with
an increase of activity in the EEG alpha frequency band measured by occipital electrodes located above
the visual cortex.

8.22 Independent linear discriminant analysis: The first step in including covariates

in EEG classification

Participants: David Trocellier, Fabien Lotte.

The classification algorithms usually used in BCI are based on an analysis called linear discriminant
analysis (LDA). Despite being the state of the art in online classification algorithm in our field, this
algorithm is known not to be robust to neuronal changes that can appear during BCI such as fatigue
or anxiety. To address these limitations, we developed a modification of the LDA algorithm, which we

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Inria Annual Report 2023

called invariant LDA (iLDA). This new model aimed to be robust to covariates known to influence BCI
control. It showed significant improvements in classification accuracy on simulated data. However, so
far, it has not demonstrated yet improvement in classification performance on real EEG data for the
covariates we tested (Fatigue, anxiety, motivation, attention). This work has been presented at national
and international conferences [55].

8.23 Riemannian ElectroCardioGraphic signal classification

Participants:

Fabien Lotte.

External collaborators:

Aurelien Appriou (Flit Sport).

Estimating mental states such as cognitive workload from ElectroCardioGraphic (ECG) signals is a key
but challenging step for many fields such as ergonomics, physiological computing, medical diagnostics or
sport training. So far, the most commonly used machine learning algorithms to do so are linear classifiers
such as Support Vector Machines (SVMs), often resulting in modest classification accuracies. However,
Riemannian Geometry-based Classifiers (RGC), and more particularly the Tangent Space Classifiers (TSC),
have recently shown to lead to state-of-the-art performances for ElectroEncephaloGraphic (EEG) signals
classification. However, RGCs have never been explored for classifying ECG signals. Therefore, in this
paper we design the first Riemannian geometry-based TSC for ECG signals, evaluate it for classifying two
levels of cognitive workload, i.e., low versus high workload, and compare results to the ones obtained
using an algorithm that is commonly used in the literature: the SVM. Our results indicated that the
proposed ECG-TSC significantly outperformed an ECG-SVM classifier (a commonly used algorithm in
the literature) when using 6, 10, 20, 30 and 40seconds time windows, suggesting an optimal time window
length of 120 seconds (65.3% classification accuracy for the TSC, 57.8% for the SVM). Altogether, our
results showed the value of RGCs to process ECG signals, opening the door to many other promising ECG
classification applications. This work was published as a conference paper in the 4th Latin-American
Workshop on Computational Neuroscience [24].

8.24 Novel SPD matrix representations considering cross-frequency coupling for

EEG classification using Riemannian geometry

Participants:

Fabien Lotte.

External collaborators: Maria Sayu Yamamoto (Univ. Paris-Saclay), Apolline Mellot (Univ.

Paris-Saclay), Sylvain Chevallier (Univ. Paris-Saclay).

Accurate classification of cognitive states from Electroencephalographic (EEG) signals is crucial in
neuroscience applications such as Brain-Computer Interfaces (BCIs). Classification pipelines based on
Riemannian geometry are often state-of-the-art in the BCI field. In this type of BCI, covariance matrices
based on EEG signals of independent frequency bands are used as classification features. However,
there is significant neuroscience evidence of neural interactions across frequency bands, such as cross-
frequency coupling (CFC). Therefore, in this paper, we propose novel symmetric positive definite (SPD)
matrix representations considering CFC for Riemannian geometry-based EEG classification. The spatial
interactions of phase and amplitude within and between frequency bands are described in three different
CFC SPD matrices. This allows us to include additional discriminative neurophysiological features that
are not available in the conventional Riemannian EEG features. Our method was evaluated using a

Project POTIOC

23

mental workload classification task from a public passive BCI dataset. Our fused model of the three CFC
covariance matrices showed statistically significant improvements in average classification accuracies
from the conventional covariance matrix in the theta and alpha bands by 18.32% and in the beta and
gamma bands by 4.34% with smaller standard deviations. This result confirmed the effectiveness of
considering more diverse neurophysiological interactions within and between frequency bands for
Riemannian EEG classification. This work was published at the EUSIPCO 2023 conference [41].

8.25 Modeling complex EEG data distribution on the Riemannian manifold toward

outlier detection and multimodal classification

Participants:

Fabien Lotte.

External collaborators: Maria Sayu Yamamoto (Univ. Paris-Saclay), Yuichi Tanaka, Toshi-
hisa Tanaka, Frédéric Dehais, Md Rabiul Islam, Khadijeh Sadatnejad.

The usage of Riemannian geometry for Brain-computer interfaces (BCIs) has gained momentum in
recent years. Most of the machine learning techniques proposed for Riemannian BCIs consider the data
distribution on a manifold to be unimodal. However, the distribution is likely to be multimodal rather than
unimodal since high-data variability is a crucial limitation of electroencephalography (EEG). In this paper,
we propose a novel data modeling method for considering complex data distributions on a Riemannian
manifold of EEG covariance matrices, aiming to improve BCI reliability. Our method, Riemannian
spectral clustering (RiSC), represents EEG covariance matrix distribution on a manifold using a graph with
proposed similarity measurement based on geodesic distances, then clusters the graph nodes through
spectral clustering. This allows flexibility to model both a unimodal and a multimodal distribution on a
manifold. RiSC can be used as a basis to design an outlier detector named outlier detection Riemannian
spectral clustering (oden-RiSC) and a multimodal classifier named multimodal classifier Riemannian
spectral clustering (mcRiSC). All required parameters of odenRiSC/mcRiSC are selected in data-driven
manner. Moreover, there is no need to pre-set a threshold for outlier detection and the number of modes
for multimodal classification. The experimental evaluation revealed odenRiSC can detect EEG outliers
more accurately than existing methods and mcRiSC outperformed the standard unimodal classifier,
especially on highvariability datasets. odenRiSC/mcRiSC are anticipated to contribute to making real-life
BCIs outside labs and neuroergonomics applications more robust. This work was published in the journal
IEEE Transactions on Biomedical Engineering [23].

9 Bilateral contracts and grants with industry

9.1 Bilateral contracts with industry

SNCF - Cifre:

Participants: Maudeline Marlier, Arnaud Prouzeau, Martin Hachet.

• Duration: 2022-2025

• Local coordinator: Arnaud Prouzeau

• We started a collaboration with SNCF around the PhD thesis (Cifre) of Maudeline Marlier. The

objective is to rethink railway control rooms with interactive tabletop projections.

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Inria Annual Report 2023

10 Partnerships and cooperations

10.1 International research visitors

10.1.1 Visits to international teams

Research stays abroad

Ambre Assor

Visited institution: Ecole de Technology Supérieur (ETS) Montréal

Country: Canada

Dates: 01/06/2023 – 01/09/2023

Context of the visit: Research visit with Michael McGuffin to work on transition between abstract and

situated visualisation in augmented reality.

Mobility program/type of mobility: Research stay cofinanced by the LaBRI AAP Générique and the ANR

Ember project.

Morgane Koval

Visited institution: University of Toronto

Country: Canada

Dates: 26/06/2023 – 14/08/2023

Context of the visit: Research visit with Fanny Chevalier to work on visualizing travel uncertainty on

maps.

Mobility program/type of mobility: Research stay cofinanced by the LaBRI AAP Générique and the ANR

Ember project.

Fabien Lotte & Marc Welter

Visited institution: Tokyo University of Agriculture and Technology (TUAT)

Country: Japan

Dates: 10/08/2023 – 28/08/2023

Context of the visit: Research stay to collaborate on Brain-Computer Interfaces in Prof. Toshihisa Tanaka

laboratory at TUAT. F. Lotte was a visiting professor there, and M. Welter a visiting PhD student.

Mobility program/type of mobility: Research stay financed by TUAT GIR (Global Innovation Research)

program.

David Trocellier

Visited institution: Nanyang Technological University (NTU)

Country: Singapore

Dates: 01/10/2023 – 31/12/2023

Context of the visit: Visit to the laboratory of Cuntai Guan (CBCR) to discover one of the leading deep
learning teams in the field of BCI and to work on the development of new classification classification
algorithms robust to factors known to have an influence on BCI control performance.

Mobility program/type of mobility: Research stay financed by the ”Académie Française” and the ”collège

des écoles doctorales” of Univ. Bordeaux.

Project POTIOC

25

10.2 European initiatives

10.2.1 Horizon Europe

CHRISTERA Project BITSCOPE :

Participants: Marc Welter, Axel Bouneau, Fabien Lotte, Jonathan Baum.

• Title: BITSCOPE: Brain Integrated Tagging for Socially Curated Online Personalised Experiences

• Duration: 2022-2025

• Partners: Dublin City (Ireland), Univ. Polytechnic Valencia (Spain), Univ. Nicolas Corpernicus

(Poland), Inria (France)

• Coordinator: Tomas Ward

• This project presents a vision for brain computer interfaces (BCI) which can enhance social rela-
tionships in the context of sharing virtual experiences. In particular we propose BITSCOPE, that
is, Brain-Integrated Tagging for Socially Curated Online Personalised Experiences. We envisage a
future in which attention, memorability and curiosity elicited in virtual worlds will be measured
without the requirement of “likes” and other explicit forms of feedback. Instead, users of our
improved BCI technology can explore online experiences leaving behind an invisible trail of neural
data-derived signatures of interest. This data, passively collected without interrupting the user, and
refined in quality through machine learning, can be used by standard social sharing algorithms
such as recommender systems to create better experiences. Technically the work concerns the
development of a passive hybrid BCI (phBCI). It is hybrid because it augments electroencephalo-
graphy with eye tracking data, galvanic skin response, heart rate and movement in order to better
estimate the mental state of the user. It is passive because it operates covertly without distracting
the user from their immersion in their online experience and uses this information to adapt the
application. It represents a significant improvement in BCI due to the emphasis on improved
denoising facilitating operation in home environments and the development of robust classifiers
capable of taking inter- and intra-subject variations into account. We leverage our preliminary
work in the use of deep learning and geometrical approaches to achieve this improvement in signal
quality. The user state classification problem is ambitiously advanced to include recognition of
attention, curiosity, and memorability which we will address through advanced machine learning,
Riemannian approaches and the collection of large representative datasets in co-designed user
centred experiments.

Inria-DFKI NEARBY :

Participants:

Fabien Lotte, Sebastien Rimbert.

• Title: Noise and Variability Free Brain-Computer Interfaces

• Duration: 2023-2027

• Partners: Inria Bordeaux (Potioc & Mnemosyne), DFKI Saarbrucken, DFKI Bremen

• Coordinators: Fabien Lotte & Maurice Rekrut

• While Brain-Computer Interfaces (BCI) are promising for many applications, e.g., assistive techno-
logies, man-machine teaming or motor rehabilitation, they are barely used uut-of-the-lab due to a
poor reliability.Electroencephalographic (EEG) brain signals are indeed very noisy and variable,
both between and within users. To address these issues, we first propose to join Inria and DFKI

26

Inria Annual Report 2023

forces to build large-scale multicentric and open EEG-BCI databases, with controlled noise and
variability sources, for BCIs based on motor and speech activity. Building on this data we will then
design new Artificial Intelligence algorithms, notably based on Deep Learning, dedicated to EEG
denoising and variability-robust EEG-decoding. Such algorithms will be implemented both on
open-source software as well as FPGA hardware, and then demonstrated in two out-of-the-lab BCI
applications: Human-Robot collaboration and exoskeleton control

10.3 National initiatives

ANR Project BeAware :

Participants: Martin Hachet, Yvonne Jansen, Pierre Dragicevic, Arnaud Prouzeau,

Fabien Lotte, Aymeric Ferron, Ambre Assor.

• Duration: 2023-2026

• Partners: CIRED, LESSAC-BSB

• Coordinator: Martin Hachet

• BeAware explores how augmented reality (AR) systems can reduce the spatial and temporal distance
between people’s choices and their environmental impact. We design interactive visualizations
that integrate concrete environmental consequences (e.g. waste accumulation, rare earth mining)
directly into people’s surroundings. This interdisciplinary research will be informed and validated
by incentivized and controlled behavioral economics experiments based on game-theoretical
models, and be guided by real environmental data and scenarios

• website: BeAware

ANR Project EMBER :

Participants:

Pierre Dragicevic, Martin Hachet, Yvonne Jansen, Arnaud Prouzeau,
Ambre Assor.

• Duration: 2020-2024

• Partners: Inria/AVIZ, Sorbonne Université

• Coordinator: Pierre Dragicevic

• The goal of the project is to study how embedding data into the physical world can help people to
get insights into their own data. While the vast majority of data analysis and visualization takes
place on desktop computers located far from the objects or locations the data refers to, in situated
and embedded data visualizations, the data is directly visualized near the physical space, object, or
person it refers to.

• website: Ember

Project POTIOC

ANR JCJC ICARE :

27

Participants:

Arnaud Prouzeau, Martin Hachet, Yvonne Jansen, Juliette Le Meudec.

• Duration: 2023-2026

• Partners: Inria/ILDa, Monash University, Queensland University

• Coordinator: Arnaud Prouzeau

• In this project, we explore the use of immersive technologies for collaborative learning. First in
fully virtual reality environments and then in heterogeneous ones which include different types of
devices (e.g. AR/VR, wall displays, desktops), we will design interaction techniques to improve how
people collaborate in practical learning activities.

• website: ICARE

ANR BCI4IA :

Participants:

Sebastien Rimbert, Fabien Lotte, Valerie Marissens.

• Duration: 2023-2027

• Partners: Inria, LORIA, CHRU Nancy, CHU Brugmann, Univ. Libre Bruxelles

• Coordinator: Claude Meistelman

• The BCI4IA project aims to design a brain-computer interface to enable reliable general anesthesia
(GA) monitoring, in particular to detect intraoperative awareness. Currently, there is no satisfactory
solution to do so whereas it causes severe post-traumatic stress disorder. "I couldn’t breathe, I
couldn’t move or open my eyes, or even tell the doctors I wasn’t asleep." This testimony shows that
a patient’s first reaction during an intraoperative awareness is usually to move to alert the medical
staff. Unfortunately, during most surgery, the patient is curarized, which causes neuromuscular
block and prevents any movement. To prevent intraoperative awareness, we propose to study motor
brain activity under GA using electroencephalography (EEG) to detect markers of motor intention
(MI) combined with general brain markers of consciousness. We will analyze a combination of
MI markers (relative powers, connectivity) under the propofol anesthetics, with a brain-computer
interface based on median nerve stimulation to amplify them. Doing so will also require to design
new machine learning algorithms based on one-class (rest class) EEG classification, since no EEG
examples of the patient’s MI under GA are available to calibrate the BCI. Our preliminary results are
very promising to bring an original solution to this problem which causes serious traumas.

• website: BCI4IA

28

ANR PROTEUS :

Inria Annual Report 2023

Participants:

Fabien Lotte, Sebastien Rimbert, Pauline Dreyer, David Trocellier.

• Duration: 2023-2027

• Partners: Inria, LAMSADE, ISAE-SupAero, Wisear

• Coordinator: Fabien Lotte

• Whereas BCI are very promising for various applications they are not reliable. Their reliability
degrades even more when used across contexts (e.g., across days, for changing users’ states or
applications used) due to various sources of variabilities. Project PROTEUS proposes to make
BCIs robust to such variabilities by 1) Systematically measuring BCI and brain signal variabilities
across various contexts while sharing the collected databases; 2) Characterising, understanding
and modelling the variability and their sources based on these new databases; and 3) Tackling these
variabilities by designing new machine learning algorithms optimally invariant to them according
to our models, and using the resulting BCIs for two practical applications affected by variabilities:
tetraplegic BCI user training and auditory attention monitoring at home or in flight.

• website: PROTEUS

AeX Inria Live-It

:

Participants:

Arnaud Prouzeau, Martin Hachet, Emma Tison, Claudia Krogmeier,
Justin Dillmann.

• Duration: 2022-2024

• Partners: Université de Bordeaux - NeuroPsychology

• Coordinator: Arnaud Prouzeau and Martin Hachet

• In collaboration with colleagues in neuropsychology (Antoinette Prouteau), we are exploring how
augmented reality can help to better explain schizophrenia and fight against stigmatization. This
project is directly linked to Emma Tison’s PhD thesis.

AeX I-Am :

Participants:

Pierre Dragicevic, Leana Petiot.

• Duration: 2023-2026

• Partners: Flower team, Université de Bordeaux - Psychology

• Coordinator: Pierre Dragicevic and Hélène Sauzéon

Project POTIOC

29

• Title: The influence of augmented reality on autobiographical memory: a study of involuntary and
false memories. Abstract: Although the Metaverse quickly raised a number of questions about
its potential benefits and dangers for humans, augmented reality (AR) has made its way into our
lives without raising such questions. The present program proposes to initiate this questioning by
evaluating the impact of AR on our autobiographical memory, i.e. the memory that characterizes
the "self" of each of us, by investigating the human and technical factors conducive to or, on the
contrary, protective of memory biases.

• website: I-am

11 Dissemination

11.1 Promoting scientific activities

11.1.1 Scientific events: organisation

General chair, scientific chair

• General Chair EnergyVis Workshop at IEEE VIS (Arnaud Prouzeau)

• General Chair Immersive Generative Design Workshop at IEEE ISMAR (Arnaud Prouzeau)

• General Chair ACM TEI’25 (Yvonne Jansen)

Member of the organizing committees

• Demo/Poster Chair ICAT-EGVE (Claudia Krogmeier)

• Workshop Chair IEEE ISMAR (Arnaud Prouzeau)

• Workshop Chair IHM (Arnaud Prouzeau)

11.1.2 Scientific events: selection

Chair of conference program committees

• IEEE VIS, Area Program Chair (Pierre Dragicevic)

Member of the conference program committees

• IEEE VIS (Arnaud Prouzeau, Yvonne Jansen)

• 4th Latin American Workshop on Computational Neuroscience (LAWCN) 2023 (Fabien Lotte)

• IEEE ICAT 2023 (Fabien Lotte)

• CORTICO Days 2023 (Fabien Lotte)

Reviewer

• Arnaud Prouzeau: IEEE VR, ACM CHI, IHM, EuroVIS, IEEE ISMAR, ACM VRST, ACM ISS

• Pierre Dragicevic: ACM CHI, JPI, ACM TOCHI, IEEE VIS, EuroVis

• Yvonne Jansen: IEEE TVCG, ACM ToCHI, ACM CHI

• Aymeric Ferron: IEEE ISMAR, ACM IHM

• Hessam Djavaherpour: ACM CHI, IEEE Vis, ACM UIST

• Fabien Lotte: Int. BCI Meeting, CORTICO, IEEE ICAT, ACM CHI, IEEE VR

• Sébastien Rimbert: IEEE SMC, CORTICO

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Inria Annual Report 2023

11.1.3 Journal

Member of the editorial boards

• Member of the editorial board of the Journal of Perceptual Imaging (JPI) (Pierre Dragicevic)

• Member of the editorial board of the Springer Human–Computer Interaction Series (HCIS) (Pierre Dra-

gicevic).

• Member of the advisory committee and editorial board of The Journal of Visualization and Interac-

tion (JoVI) (Yvonne Jansen)

• Member of the editorial board (Associate Editor) of the Journal Brain-Computer Interfaces (Fa-

bien Lotte)

• Member of the editorial board (Associate Editor) of the Journal IEEE Transactions on Biomedical

Engineering (Fabien Lotte)

• Member of the editorial board of Journal of Neural Engineering (Fabien Lotte)

• Member of the editorial board (co-specialty chief editor) of Frontiers in Neuroergonomics, section

Neurotechnology and Systems Neuroergonomics (Fabien Lotte)

Reviewer - reviewing activities

• Fabien Lotte: Frontiers in Human Neuroscience

• Sébastien Rimbert: Frontiers in Human Neuroscience, Frontiers in Neuroscience, PeerJ, Sensors

• Marc Welter: Journal of Perceptual Imaging

11.1.4 Invited talks

• Hessam Djavaherpour: Invited for a talk at the ATLAS Institute, University of Colorado Boulder.

• Fabien Lotte:

– "Towards understanding and tackling variabilities in Brain-Computer Interactions", Univ.

Essex BCI Lab online BCI lectures series, online, Inaugural invited talk, December 2023

– "On Variabilities Affecting Brain-Computer Interactions", 4th Latin-American Workshop on

Computational Neursocience, Envigado, Colombia, closing keynote, November 2023

– "Can Neurotechnologies contribute to global Peace?", USERN Virtual congress 2023, online,

invited talk, November 2023

– “Brain-computer Interface-based Motor and Cognitive Rehabilitation”, NCU-RIKEN Workshop

on Complex System for Health, Torun, Poland, invited plenary talk, Sept. 2023

– "Machine Learning, Human Factors and Software solutions for out-of-the-lab BCI use", MBT

Conference 2.0: Methods in Mobile EEG, Belgrade, Serbia, Keynote, Sept. 2023

– "Comprendre et dompter les variabilités dans les interactions cerveau-ordinateur", Neuro-

technologies Master Class France, online, invited plenary talk, Sept. 2023.

– “Machine Learning methods to decode cognitive, affective and conative states from EEG
signals”, IntEr-HRI Competition (Intrinsic Error Evaluation during Human -Robot Interaction),
IJCAI 2023, Macao/online, keynote, August 2023

– "Passive Brain-Computer Interfaces for cognitive, perceptive, affective and conative states

estimation", invited seminar, Macnica company, Tokyo, Japan, August 2023

– "Towards understanding and tackling variabilities in Brain-Computer Interactions", Tokyo

University of Agriculture and Technology, invited lecture, Tokyo, Japan, August 2023

Project POTIOC

31

– « Interagir avec des environnements réels ou virtuels par l’activité cérébrale: promesses,

fantasmes et réalité », Colloque EPIQUE, Paris, France, keynote, July 2023

– « Les Interfaces Cerveau-Ordinateur », « Digital Natives », le colloque MMI Bordeaux, Bordeaux,

May 2023

– "Machine and User learning aspects in Sensorimotor Brain-Computer Interface design", Re-
search Training Group Neuromodulation kick-off workshop, keynote, University of Oldenburg,
invited plenary talk, Oldenburg, Germany, March 2023

– "Addressing within-subject BCI variability with Riemannian classifiers", ISAE-Supaéero,

Toulouse, France, January 2023

• Marc Welter: Decoding Aeshthetic Preference with multi-modal passive BCI, HYBRID, IRISA,

Rennes, France, June 2023

• Sébastien Rimbert: Towards a better understanding of ERD and ERS in the context of BCI, Cuttin-

gEEG Conference, Lyon, France, Octobre 2023

Invited Poster:

• M. Welter & F. Lotte, ’EEG Oscillatory Correlates of Aesthetic Experience’, Second International
Workshop on Complex Systems Science and Health Neuroscience, Torun, Poland, September 2023
(Marc Welter, Fabien Lotte)

11.1.5 Scientific expertise

Hiring committes

• Prof. Ecole Centrale Nantes (Martin Hachet)

• Prof. Ecole Centrale Lyon (Martin Hachet)

• Prof. Univ. Copenhagen (Martin Hachet)

• Member of Search Committee for Univ. Copenhagen (Pierre Dragicevic)

Funded project reviewing

• Scientific monitor for European FET project TOUCHLESS (Pierre Dragicevic)

11.1.6 Research administration

• President ”Commission des Emplois de Recherche”, Inria Bordeaux (Martin Hachet)

• Member of the “Commission des Emplois Recherche”, Innria Bordeaux (Fabien Lotte)

• Bureau du Hub France de ”Australian-French Association for Research and Innovation (AFRAN)”

(Arnaud Prouzeau)

• Member of the CER (Comité d’Éthique de la Recherche) Paris-Saclay (Pierre Dragicevic, Yvonne Jansen)

• Member of the CER Université de Bordeaux (Pierre Dragicevic, Yvonne Jansen)

• Co-departement leader of the Image & Sound department at LaBRI (Yvonne Jansen)

• Member of the scientic council of LaBRI (Yvonne Jansen, Aymeric Ferron)

• Member of the council of the EDMI doctoral school (Aymeric Ferron)

• Members of the governing board of CORTICO, the French association for BCI research (www.cortico.fr)

(Fabien Lotte, Sebastien Rimbert)

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Inria Annual Report 2023

11.2 Teaching - Supervision - Juries

11.2.1 Teaching

• Doctoral School: Interaction, Réalité Virtuelle et Réalité augmentée, 12h eqTD, EDMI, Université

de Bordeaux (Martin Hachet)

• Master: Unity programing, 9h, M2 Université de Bordeaux (Vincent Casamayou)

• Master: Réalité Virtuelle, 12h eqTD, M2 Cognitive science, Université de Bordeaux (Martin Hachet)

• Master: Réalité Virtuelle, 3h eqTD, M2 Cognitive science, Université de Bordeaux (Arnaud Prouzeau)

• Master: Réalités Virtuelles et augmentées, 12h eqTD, M2 Computer science, Université de Bordeaux

(Martin Hachet)

• Master: Neuroergonomie, 5h eqTD, M2 Cognitive science, Université de Bordeaux (Fabien Lotte)

• Master: Neuroergonomie, 2h eqTD, M2 Cognitive science, Université de Bordeaux (Sébastien Rim-

bert)

• Master: Augmented Reality, 15h eqTD, M2 Image Processing and Computer Vision (IPCV), Uni-

versité de Bordeaux (Arnaud Prouzeau)

• Master: Facteurs Humains et Interactions Humain-Machine, 22h eqTD, M1 Cognitive science,

Université de Bordeaux (Arnaud Prouzeau)

• Master: supervision of an end of studies project (3D object morphing) of Master 2 of University of

Bordeaux, January-february-march 2023 (Ambre Assor)

• Master: Système de Gestion de Base de Données, 20h eqTD, 2A Filière Informatique, ENSEIRB-

MATMECA (Bordeaux INP) (Aymeric Ferron)

• Master: Projet de programmation orienté objet en Java, 1A Filière Informatique, ENSEIRB-MATMECA

(Morgane Koval)

• Master: Affective Decoding in/for Design, 6h, M2 Design, Université de Bordeaux Montaigne

(Marc Welter)

• Bachelor: projet de développement logiciel, 29h, Université de Bordeaux (Edwige Chauvergne)

• Bachelor: Travaux encadrée de recherche, 10h eqTD, L3,Université de Bordeaux (David Trocellier)

• Bachelor: Perception action, 20 eqTD, L2, Université de Bordeaux (David Trocellier)

• Bachelor: Introduction a la programmation, 32 eqTD, L1, Université de Bordeaux (David Trocellier)

• Bachelor: Méthode de l’évaluation, L3 Psychologie, 24h eqTD, Université de Bordeaux (Emma Tison)

• Bachelor: Traitement de données, L2 Psychologie, 12h eqTD, Université de Bordeaux (Emma Tison)

• Bachelor: Introduction à la neuropsychologie, L1 Psychologie, 16h eqTD, Université de Bordeaux

(Emma Tison)

• Bachelor: Tutorat informatique, Licence Pro Médiateurs santé pairs, 12h eqTD, Université de

Bordeaux (Emma Tison)

• Bachelor: Design Workshop, L’art de video et le montage video, 12h, Université de Bordeaux,

octobre 2023 (Claudia Krogmeier)

• Bachelor: Projet d’algorithmique et de programmation, 24h, 1A Filière Informatique, ENSEIRB-

MATMECA (Bordeaux INP) (Aymeric Ferron)

Project POTIOC

33

• Bachelor: Projet de programmation en C, 1A Filière Informatique, ENSEIRB-MATMECA (Mor-

gane Koval)

• Engineering school: Immersion and interaction with visual worlds, 7,5h eqtd, Graduate Degree Arti-
ficial Intelligence and Advanced Visual Computing, Ecole Polytechnique Palaiseau (Arnaud Prouzeau)

• Engineering school: Immersion and interaction with visual worlds, 4,5h eqtd, Graduate Degree
Artificial Intelligence and Advanced Visual Computing, Ecole Polytechnique Palaiseau (Fabien Lotte

• Engineering school: Object-oriented programming, 34h, S3 ENSEIRB MATMECA (Morgane Koval)

• Supervision of interns from 3ème (9th grade) (Edwige Chauvergne, Aymeric Ferron, Maudeline Marlier,

Vincent Casamayou, Pauline Dreyer, . . . )

11.2.2 Supervision

PhD theses

• Martin Hachet: Ambre Assor (33%), Maudeline Marlier (50%), Edwige Chauvergne (50%), Aymeric

Ferron (33%), Vincent Casamayou (50%), Emma Tison (50%), Juliette Le Meudec (33%).

• Arnaud Prouzeau: Edwige Chauvergne (50%), Maudeline Marlier (50%), Juliette Le Meudec (33%),

Ambre Assor (33%).

• Pierre Dragicevic: Léana Petiot (50%), Ambre Assor (33%), Aymeric Ferron (33%).

• Yvonne Jansen: Clara Rigaud (50%), Morgane Koval (100%), Aymeric Ferron (33%)

• Fabien Lotte: David Trocellier (50%), Marc Welter (100%), Pauline Dreyer (100%), Come Annic-

chiarico (33%), Valerie Marissens (33%), Maria Sayu Yamamoto (15%)

• Sebastien Rimbert: Valerie Marissens (33%)

Master’s internships

• Pierre Dragicevic: Léana Petiot (50%).

• Yvonne Jansen: Aymeric Ferron (50%).

• Martin Hachet: Aymeric Ferron (50%).

• Sébastien Rimbert: Loic Bechon (66%).

• Fabien Lotte: Loic Bechon (33%), Juliette Meunier (33%), Jonathan Baum (33%), Ines Audinet (10%)

• David Trocellier: Juliette Meunier (66%)

• Marc Welter: Jonathan Baum (66%), Ines Audinet (90%)

11.2.3 Juries

PhD juries with report (rapporteur)

• Emmanuel Courtoux Univ. Paris-Saclay (Martin Hachet)

• Maurice RekRut, Univ. Saarland, Germany (Fabien Lotte)

• Tsvetomira Tsoneva, Donders Institute, The Netherlands (Fabien Lotte)

• Oleksandr Zlatov, TU Berlin, Germany (Fabien Lotte)

• Leena Andersen, TU Branderburgen, Germany (Fabien Lotte)

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Inria Annual Report 2023

PhD juries without report (examinateur)

• Emilie Yu, Université Nice Côte d’Azur (Martin Hachet)

• Nicolas Delcombel, IMT Atlantique (Arnaud Prouzeau)

• Laura Pruszko, Université Grenoble Alpes (Pierre Dragicevic)

• Xiaoqi Xu, ISae-SupAero, France (Fabien Lotte)

• Ambre Assor, Univ. Bordeaux, France (Fabien Lotte)

PhD follow-up committees (suivi de thèse)

• Clément Truillet, Université Toulouse 3 - Paul-Sabatier (Pierre Dragicevic)

• Pierre Vaslin, Université de Nantes (Pierre Dragicevic)

• Melvin Even, Université de Bordeaux (Arnaud Prouzeau)

• Hugo Laurent, Université de Bordeaux (Martin Hachet)

• Anais Pontiggia, Univ. Paris / Sorbonne Univ. / PSL (Fabien Lotte)

• Clementine Jacques, Univ. Paris / Sorbonne Univ. / PSL (Fabien Lotte)

• Marcel Hinns, Isaé-Supaéro (Fabien Lotte)

• Maxime Adolphe, Univ. Bordeaux (Fabien Lotte)

• Naomi Chaix Eichel, Univ. Bordeaux (Fabien Lotte)

• Maeva Andriantsoamberomanga, Univ. Bordeaux (Fabien Lotte)

• Subba Reddy Oota, Univ. Bordeaux (Fabien Lotte)

11.3 Popularization

11.3.1 Articles and contents

• “Réalité virtuelle et santé mentale : exit le divan, place au casque ?” The Conversation (Emma Tison)

• “Using Experimental Filmmaking to Create an Engaging Brain-Computer Interface.” SIGGRAPH

(Claudia Krogmeier)

11.3.2 Education

• Yvonne Jansen and Pierre Dragicevic maintain the data physicalization wiki and the list of physical

visualizations and related artefacts.

11.3.3 Interventions

• ”Fête de la science” for pupils from primary to high school, 9-13 October 2023 (Vincent Casamayou,

Aymeric Ferron, Maudeline Marlier)

• “Immersion dans les troubles du spectre schizophrénique au moyen de la réalité augmentée”, Pitch

de thèse, Forum des Sciences Cognitives, April 2023 (Emma Tison)

• Using Augmented Reality to Reduce Stigma Towards Schizophrenia, Scientifique Psychédélique

Aquitaine, October 2023 (Claudia Krogmeier)

• “Marché des connaissances”, general public, January 21, 2023 (Aymeric Ferron)

Project POTIOC

35

• “Correspondances”, 6-year-old pupils in elementary school, March 31, 2023 (Aymeric Ferron, Ed-

wige Chauvergne)

• “Hackathon autour de l’investigation sur les algorithmes”, students in journalism, computer science

and information science, November 30, 2023 (Aymeric Ferron)

• MIMM "Moi informaticienne, moi mathématicienne” is an initiative of the University of Bordeaux,
supported by the IMB. Its aim is to introduce middle and high school girls to the digital sciences
and let them spend a week in the world of research. Presentation of the BCI / academic degree /
research-experiments / questions-answers) 30 min carried out on Monday 06/02, Tuesday 07/02,
Friday 10/02/2023 (Pauline Dreyer)

• BCI presentation for third-year ENSC students visiting Inria on Monday 25/09 (Pauline Dreyer)

• ’Art ou Science, pourquoi chosir?’, Semaine du cerveau, Bordeaux, France (Marc Welter)

• Organization of a Board games and cognitive science booth at the Cognitive Science Forum in Paris.

(David Trocellier)

• Co-organizer of the Robotics and AI Hackathon, Hack1Robo, held in the Fab Lab at Cap Sciences

(Bordeaux). 30 participants (David Trocellier)

12 Scientific production

12.1 Major publications

[1] C. Benaroch, K. Sadatnejad, A. Roc, A. Appriou, T. Monseigne, S. Pramij, J. Mladenovi´c, L. Pillette, C.
Jeunet and F. Lotte. ‘Long-Term BCI Training of a Tetraplegic User: Adaptive Riemannian Classifiers
and User Training’. In: Frontiers in Human Neuroscience 15 (18th Mar. 2021). DOI: 10.3389/fnhum
.2021.635653. URL: https://hal.inria.fr/hal-03175115.

[2]

[3]

J. Frey, M. Daniel, J. Castet, M. Hachet and F. Lotte. ‘Framework for Electroencephalography-based
Evaluation of User Experience’. In: CHI ’16 - SIGCHI Conference on Human Factors in Computing
System. Ed. by ACM. San Jose, United States, May 2016. DOI: 10.1145/2858036.2858525. URL:
https://hal.inria.fr/hal-01251014.

J. Frey, R. Gervais, S. Fleck, F. Lotte and M. Hachet. ‘Teegi: Tangible EEG Interface’. In: UIST-ACM
User Interface Software and Technology Symposium. Honolulu, United States: ACM, Oct. 2014. URL:
https://hal.inria.fr/hal-01025621.

[4] D. Furio, S. Fleck, B. Bousquet, J.-P. Guillet, L. Canioni and M. Hachet. ‘HOBIT: Hybrid Optical
Bench for Innovative Teaching’. In: CHI’17 - Proceedings of the 2017 CHI Conference on Human
Factors in Computing Systems. Denver, United States, May 2017. DOI: 10.1145/3025453.3025789.
URL: https://hal.inria.fr/hal-01455510.

[5] A. Genay, A. Lécuyer and M. Hachet. ‘Being an Avatar "for Real": a Survey on Virtual Embodiment in
Augmented Reality’. In: IEEE Transactions on Visualization and Computer Graphics (2021), pp. 1–20.
DOI: 10.1109/tvcg.2021.3099290. URL: https://hal.inria.fr/hal-03320680.

[6] M. Hachet, J.-B. De La Rivière, J. Laviole, A. Cohé and S. Cursan. ‘Touch-Based Interfaces for
Interacting with 3D Content in Public Exhibitions’. In: IEEE Computer Graphics and Applications
33.2 (Mar. 2013), pp. 80–85. DOI: 10.1109/MCG.2013.34. URL: http://hal.inria.fr/hal-007
89500.

[7]

J. Jankowski and M. Hachet. ‘A Survey of Interaction Techniques for Interactive 3D Environments’.
In: Eurographics 2013 - STAR. Girona, Spain, May 2013. URL: https://hal.inria.fr/hal-0078
9413.

[8] C. Jeunet, B. N’Kaoua and F. Lotte. ‘Advances in User-Training for Mental-Imagery Based BCI
Control: Psychological and Cognitive Factors and their Neural Correlates’. In: Progress in brain
research (Feb. 2016). URL: https://hal.inria.fr/hal-01302138.

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Inria Annual Report 2023

[9] M. Koval and Y. Jansen. ‘Do You See What You Mean? Using Predictive Visualizations to Reduce
Optimism in Duration Estimates’. In: CHI 2022 - Conference on Human Factors in Computing
Systems. New Orleans, United States, 30th Apr. 2022. DOI: 10.1145/3491102.3502010. URL:
https://inria.hal.science/hal-03599998.

[10] F. Lotte, F. Larrue and C. Mühl. ‘Flaws in current human training protocols for spontaneous Brain-
Computer Interfaces: lessons learned from instructional design’. In: Frontiers in Human Neuros-
ciences 7.568 (Sept. 2013). DOI: 10.3389/fnhum.2013.00568. URL: http://hal.inria.fr/hal-
00862716.

[11] L. Pillette, C. Jeunet, B. Mansencal, R. N’Kambou, B. N’Kaoua and F. Lotte. ‘A physical learning
companion for Mental-Imagery BCI User Training’. In: International Journal of Human-Computer
Studies 136 (Apr. 2020). 102380. DOI: 10.1016/j.ijhcs.2019.102380. URL: https://hal.inri
a.fr/hal-02434157.

[12] A. Roc, L. Pillette, J. Mladenovi´c, C. Benaroch, B. N’Kaoua, C. Jeunet and F. Lotte. ‘A review of
user training methods in brain computer interfaces based on mental tasks’. In: Journal of Neural
Engineering (2020). DOI: 10.1088/1741-2552/abca17. URL: https://hal.archives-ouverte
s.fr/hal-03009841.

[13] K. Sauvé, P. Dragicevic and Y. Jansen. ‘Edo: A Participatory Data Physicalization on the Climate
Impact of Dietary Choices’. In: TEI 2023 - 17th International Conference on Tangible Embedded
and Embodied Interaction. Warsaw (POLAND), Poland: ACM, 26th Feb. 2023. URL: https://inri
a.hal.science/hal-03906849.

[14]

[15]

J. Sol Roo, R. Gervais, J. Frey and M. Hachet. ‘Inner Garden: Connecting Inner States to a Mixed
Reality Sandbox for Mindfulness’. In: CHI ’17 - International Conference of Human-Computer
Interaction. CHI ’17. ACM. Denver, United States: ACM, May 2017. DOI: 10.1145/3025453.30257
43. URL: https://hal.archives-ouvertes.fr/hal-01455174.

J. Sol Roo and M. Hachet. ‘One Reality: Augmenting How the Physical World is Experienced by
combining Multiple Mixed Reality Modalities’. In: UIST 2017 - 30th ACM Symposium on User
Interface Software and Technology. ACM. Quebec City, Canada, Oct. 2017. DOI: 10.1145/3126594
.3126638. URL: https://hal.archives-ouvertes.fr/hal-01572490.

12.2 Publications of the year

International journals

[16] A. Assor, A. Prouzeau, M. Hachet and P. Dragicevic. ‘Handling Non-Visible Referents in Situated
Visualizations’. In: Transactions on Visualization & Computer Graphics (TVCG) (25th Oct. 2023).
URL: https://inria.hal.science/hal-04176381.

[17] P.-A. Cinquin, P. Guitton and H. Sauzéon. ‘Towards Truly Accessible MOOCs for Persons with
Cognitive Impairments: A Field Study’. In: Human-Computer Interaction 38.5-6 (10th May 2023).
DOI: 10.1080/07370024.2021.2008250. URL: https://inria.hal.science/hal-03435461.

[18] H. Djavaherpour, L. Moorman, F. Samavati and Y. Jansen. ‘First Insights into INTUIT: An INteractive
Tactile Physicalization for User Interpretation of RADAR Technology’. In: IEEE Computer Graphics
and Applications 43.5 (14th Sept. 2023), pp. 91–98. DOI: 10 . 1109 / MCG . 2023 . 3286228. URL:
https://hal.science/hal-04181117.

[19] P. Dreyer, A. Roc, L. Pillette, S. Rimbert and F. Lotte. ‘A large EEG database with users’ profile
information for motor imagery brain-computer interface research’. In: Scientific Data 10.1 (Sept.
2023), p. 580. DOI: 10.1038/s41597-023-02445-z. URL: https://inria.hal.science/hal-0
4197139.

[20] B. Oral, P. Dragicevic, A. Telea and E. Dimara. ‘Decoupling Judgment and Decision Making: A
Tale of Two Tails’. In: IEEE Transactions on Visualization and Computer Graphics (2023). DOI:
10.1109/TVCG.2023.3346640. URL: https://hal.science/hal-04354869.

Project POTIOC

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[21]

[22]

S. Rimbert and S. Fleck. ‘Long-term kinesthetic motor imagery practice with a BCI: Impacts on user
experience, motor cortex oscillations and BCI performances’. In: Computers in Human Behavior
146 (29th Apr. 2023), p. 107789. DOI: 10.1016/j.chb.2023.107789. URL: https://inria.hal
.science/hal-04093422.

S. Rimbert, J. Lelarge, P. Guerci, S. J. Bidgoli, C. Meistelman, G. Cheron, A. M. Cebolla Alvarez and
D. Schmartz. ‘Detection of Motor Cerebral Activity After Median Nerve Stimulation During General
Anesthesia (STIM-MOTANA): Protocol for a Prospective Interventional Study’. In: JMIR Research
Protocols 12 (2023), e43870. DOI: 10.2196/43870. URL: https://inria.hal.science/hal-039
70975.

[23] M. S. Yamamoto, K. Sadatnejad, T. Tanaka, M. R. Islam, F. Dehais, Y. Tanaka and F. Lotte. ‘Mod-
eling complex EEG data distribution on the Riemannian manifold toward outlier detection and
multimodal classification’. In: IEEE Transactions on Biomedical Engineering (2023). DOI: 10.1109
/TBME.2023.3295769. URL: https://hal.science/hal-04181396.

International peer-reviewed conferences

[24] A. Appriou and F. Lotte. ‘Riemannian ElectroCardioGraphic signal classification’. In: Proceedings
of the4th Latin-American Workshop on Computational Neuroscience. LAWCN 2023 - IV Latin-
American Workshop on Computational Neuroscience. Envigado, Colombia, 28th Nov. 2023. URL:
https://inria.hal.science/hal-04372193.

[25] A. Assor, A. Prouzeau, P. Dragicevic and M. Hachet. ‘Exploring Augmented Reality Waste Data
Representations for Eco Feedback.’ In: CHI EA ’23: Extended Abstracts of the 2023 CHI Conference
on Human Factors in Computing Systems. CHI 2023 - Conference on Human Factors in Computing
Systems. Hambourg, Germany: ACM, 19th Apr. 2023, pp. 1–4. DOI: 10.1145/3544549.3583905.
URL: https://inria.hal.science/hal-04096517.

[26] E. Chauvergne. ‘Understanding the Challenges of Immersive Authoring for End-Users’. In: IHM
2023 - 34ème Conférence Internationale Francophone sur l’Interaction Humain-Machine. Troyes,
France, 3rd Apr. 2023. URL: https://hal.science/hal-04042308.

[27] E. Chauvergne, M. Hachet and A. Prouzeau. ‘Authoring Interactive and Immersive Experiences
Using Programming by Demonstration’. In: Proceedings of the 34th Conference on l’Interaction
Humain-Machine (IHM ’23). IHM 2023 - 34ème Conférence Internationale Francophone sur
l’Interaction Humain-Machine. Troyes (France), France, 3rd Apr. 2023. DOI: 10.1145/358396
1.3583981. URL: https://hal.science/hal-04013866.

[28] E. Chauvergne, M. Hachet and A. Prouzeau. ‘User Onboarding in Virtual Reality: An Investigation
of Current Practices’. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing
Systems (CHI ’23). CHI 2023 - Conference on Human Factors in Computing Systems. Hamburg,
Germany, 24th Apr. 2023. DOI: 10.1145/3544548.3581211. URL: https://hal.science/hal-
04009287.

[29] K.-T. Chen, A. Prouzeau, J. Langmead, R. Whitelock-Jones, L. Lawrence, T. Dwyer, C. Hurter, D.
Weiskopf and S. Goodwin. ‘Gazealytics: A Unified and Flexible Visual Toolkit for Exploratory and
Comparative Gaze Analysis’. In: ETRA 2023 - ACM Symposium on Eye Tracking Research and
Applications. 69. Tubingen, Germany: ACM, 23rd May 2023, pp. 1–7. DOI: 10.1145/3588015.3589
844. URL: https://enac.hal.science/hal-04144751.

[30] B. Lee, A. Satyanarayan, M. Cordeil, A. Prouzeau, B. Jenny and T. Dwyer. ‘Deimos: A Grammar
of Dynamic Embodied Immersive Visualisation Morphs and Transitions’. In: CHI 2023 - CHI
Conference on Human Factors in Computing Systems. 810. Hamburg, Germany: ACM, 23rd Apr.
2023, pp. 1–18. DOI: 10.1145/3544548.3580754. URL: https://hal.science/hal-04117248.

[31]

J. Liu, B. Ens, A. Prouzeau, J. Smiley, I. K. Nixon, S. Goodwin and T. Dwyer. ‘DataDancing: An
Exploration of the Design Space For Visualisation View Management for 3D Surfaces and Spaces’.
In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. CHI 2023 -
CHI Conference on Human Factors in Computing Systems. Hamburg, Germany: ACM, 23rd Apr.
2023, pp. 1–17. DOI: 10.1145/3544548.3580827. URL: https://hal.science/hal-04117262.

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[32] R. Otono, A. Genay, M. Perusquía-Hernández, N. Isoyama, H. Uchiyama, M. Hachet, A. Lécuyer and
K. Kiyokawa. ‘I’m Transforming! Effects of Visual Transitions to Change of Avatar on the Sense of
Embodiment in AR’. In: 2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR). VR 2023 -
IEEE Conference on Virtual Reality and 3D User Interfaces. Shanghai, China, Mar. 2023, pp. 83–93.
URL: https://inria.hal.science/hal-03968274.

[33] V. P. Martin, A. Ferron, J.-L. Rouas and P. Philip. ‘“Prediction of Sleepiness Ratings from Voice by Man
and Machine”: A Perceptual Experiment Replication Study’. In: ICASSP 2023 - IEEE International
Conference on Acoustics, Speech and Signal Processing. 2023 IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP). Ixia-Ialyssos, Greece: IEEE, 4th June 2023. DOI:
10.1109/ICASSP49357.2023.10096193. URL: https://hal.science/hal-04124477.

[34] V. P. Martin, A. Ferron, J.-L. Rouas, T. Shochi, L. Dupuy and P. Philip. ‘Physiological vs. Subjective
sleepiness: what can human hearing estimate better?’ In: ICPhS 2023 - 20th International Congress
of Phonetic Sciences. Proceedings of the 20th International Congress of Phonetic Sciences, Prague
2023. Prague, Czech Republic, 7th Aug. 2023, pp. 196–200. URL: https://hal.science/hal-041
80703.

[35] V. P. Martin, J.-L. Rouas, A. Ferron and P. Philip. ‘"Prediction of sleepiness ratings from voice by man
and machine" : the Endymion replication perceptual study’. In: ICPhS 2023 - 20th International
Congress of Phonetic Sciences. Proceedings of the 20th International Congress of Phonetic Sciences,
Prague 2023. Prague, Czech Republic: GUARANT International spol., 7th Aug. 2023, pp. 201–205.
URL: https://hal.science/hal-04180701.

[36] C. Rigaud, G. Bailly and Y. Jansen. ‘Knowledge Resources in Fabrication Workshops : Objectives
and Challenges’. In: Proceedings of the 34th Conference on l’Interaction Humain-Machine. IHM’23:
34ème Conférence Internationale Francophone sur l’Interaction Humain-Machine. Troyes, France:
ACM, 3rd Apr. 2023, pp. 1–13. DOI: 10.1145/3583961.3583974. URL: https://hal.sorbonne-u
niversite.fr/hal-04015740.

[37] S. Rimbert, D. Trocellier and F. Lotte. ‘Impact of the baseline temporal selection on the ERD/ERS
analysis for Motor Imagery-based BCI’. In: EMBC 2023 - 45th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society. Sydney, Australia, 24th July 2023. URL:
https://inria.hal.science/hal-04077693.

[38] K. Sauvé, P. Dragicevic and Y. Jansen. ‘Edo: A Participatory Data Physicalization on the Climate
Impact of Dietary Choices’. In: TEI 2023 - 17th International Conference on Tangible Embedded
and Embodied Interaction. Warsaw (POLAND), Poland: ACM, 26th Feb. 2023. URL: https://inri
a.hal.science/hal-03906849.

[39] A. Verma, L. Morais, P. Dragicevic and F. Chevalier. ‘Designing Resource Allocation Tools to Promote
Fair Allocation: Do Visualization and Information Framing Matter?’ In: CHI 2023 - Conference on
Human Factors in Computing Systems. Hamburg, Germany: ACM, 23rd Apr. 2023. DOI: 10.1145/3
544548.3580739. URL: https://inria.hal.science/hal-04074164.

[40] W. Wei, S. Huron and Y. Jansen. ‘Towards Autocomplete Strategies for Visualization Construction’.
In: Proceedings of 2023 IEEE Conference on Visualization and Visual Analytics (VIS). 2023 IEEE
Visualization and Visual Analytics (VIS). Melbourne, Australia: IEEE, 21st Oct. 2023, pp. 141–145.
DOI: 10.1109/vis54172.2023.00037. URL: https://inria.hal.science/hal-04394592.

[41] M. S. Yamamoto, A. Mellot, S. Chevallier and F. Lotte. ‘Novel SPD matrix representations considering
cross-frequency coupling for EEG classification using Riemannian geometry’. In: EUSIPCO 2023 -
The 31st European Signal Processing Conference. Helsinki, Finland, 4th Sept. 2023. URL: https:
//hal.science/hal-04131609.

Conferences without proceedings

[42] Y. Jansen, A. Assor, P. Dragicevic, A. Ferron, A. Prouzeau, M. Hachet, T. Le Gallic, I. Ajdukovic,
E. Montagner, E. Spiegelman and A. Sutan. ‘An Interdisciplinary Approach to Designing and
Evaluating Data-Driven Interactive Experiences for Sustainable Decision-Making’. In: Workshop
on HCI for Climate Change at CHI 2023. Hamburg, Germany, 28th Apr. 2023. DOI: 10.5281/zenod
o.7961762. URL: https://inria.hal.science/hal-04103414.

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Scientific book chapters

[43] M. Le Goc, C. Perin, S. Follmer, J.-D. Fekete and P. Dragicevic. ‘Zooids’. In: Making with Data:
Physical Design and Craft in a Data-Driven World. A K Peters/CRC Press, 2023. URL: https://inr
ia.hal.science/hal-03978632.

Doctoral dissertations and habilitation theses

[44] P. Dragicevic. ‘Small Data - Visualizing Simple Datasets for Communication and Decision Making’.
Université de Bordeaux (UB), 23rd June 2023. URL: https://inria.hal.science/tel-0435269
9.

Reports & preprints

[45] A. Assor, A. Prouzeau, P. Dragicevic and M. Hachet. Augmented Reality Waste Accumulation Visual-

izations. 8th Mar. 2023. URL: https://hal.science/hal-03907474.

[46] A. Ferron. Raising awareness of the impacts of eating habits on the environment: a data visualization
exploration. RR-9512. Inria Centre at the University of Bordeaux, 15th June 2023. URL: https://ha
l.science/hal-04129393.

Other scientific publications

[47] M. Alimardani, V. Gamboa von Groll, N. Leeuwis, S. Rimbert, A. Roc, L. Pillette and F. Lotte. ‘Does
Gender Matter in Motor Imagery BCIs?’ In: BCI Meeting 2023 - 10th International Balancing
Innovation and Translation Meeting. Brussels, Belgium, 6th June 2023. DOI: 10.5281/zenodo.751
6451. URL: https://inria.hal.science/hal-04126907.

[48] V. Casamayou, L. Canioni and M. Hachet. ‘HQBIT: Performing quantum optics practical work in
a hybrid environment’. In: ICERI 2023 - International Conference of Education, Research and
Innovation. Seville, Spain, 13th Nov. 2023. URL: https://hal.science/hal-04214530.

[49] P. Dreyer, A. Roc, S. Rimbert, F. Lotte and L. Pillette. ‘DUPE MIBCI: Database with User’s Profile and
EEG signals for Motor Imagery Brain Computer Interface research’. In: BCI 2023 - 10th International
BCI Meeting Balancing Innovation and Translation. Bruxelles, Belgium, 6th June 2023. URL: https:
//hal.science/hal-04125666.

[50] C. Letondal, A. Tabard, L. Bornes, A. Esteves, M. Hachet, V. Maquil and A. Roudaut. Tangible
Interaction and Industrial Degrowth: Follow-up of a panel on environmental issues in tangible
interfaces at ETIS 2022. 28th Apr. 2023. URL: https://enac.hal.science/hal-04076777.

[51] S. Rimbert. ‘Improving motor imagery detection with a BCI based on somesthetic non invasive
stimulations’. In: 10th International BCI Meeting Balancing Innovation and Translation. Bruxelles,
Belgium, 6th June 2023. URL: https://inria.hal.science/hal-04030312.

[52] S. Rimbert, V. Marissens Cueva, M. Petieau, Z. Cheffi, G. M. Cheron, S. J. Bidgoli, A. M. Cebolla
Alvarez and D. Schmartz. ‘Detection of Cerebral Electroencephalographic Patterns After Median
Nerve Stimulation During Propofol-Induced General Anesthesia : a Prospective Interventional
Cohort Study’. In: Anesthesiology annual meeting 2023. San Francisco, United States, 13th Oct.
2023. URL: https://inria.hal.science/hal-04201221.

[53] A. Roc and F. Lotte. ‘What can we learn from user interviews in BCI sessions?’ In: BCI 2023 - 10th
International BCI Meeting Balancing Innovation and Translation. Bruxelles (BE), Belgium, 6th June
2023. URL: https://inria.hal.science/hal-04125216.

[54] D. Trocellier, B. N’Kaoua and F. Lotte. ‘Independent linear discriminant analysis : The first step
in including covariates in EEG classification’. In: CORTICO 2023 - COllectif pour la Recherche
Transdisciplinaire sur les Interfaces Cerveau-Ordinateur. Paris, France, 9th May 2023. URL: https:
//hal.science/hal-04118675.

[55] D. Trocellier, B. N’Kaoua and F. Lotte. ‘Towards including covariates in EEG classification -a prelim-
inary study on simulated data’. In: BCI Meeting 2023 - 10th International BCI Meeting. Bruxelles
(BE), Belgium, 6th June 2023. URL: https://hal.science/hal-04031671.

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[56] M. Welter and F. Lotte. EEG Oscillatory Correlates Of Aesthetic Experience -A Review. Brussels,

Belgium, 6th June 2023. URL: https://inria.hal.science/hal-04030297.

[57] M. S. Yamamoto, S. Chevallier and F. Lotte. ‘Effectiveness of cross-frequency phase-amplitude
covariance as additional features for Riemannian BCIs’. In: BCI 2023 - 10th International BCI
Meeting Balancing Innovation and Translation. Brussels, Belgium, 6th June 2023. DOI: 10.3217/97
8-3-85125-962-9-179. URL: https://hal.science/hal-04181391.

12.3 Cited publications

[58] T. Lauren, N. Rodier, B. Oriola, M. Hachet, C. Jouffrais and A. Brock. ‘Inclusive Adaptation of Existing
Board Games for Gamers with and without Visual Impairments using a Spatial Augmented Reality
Framework for Touch Detection and Audio Feedback’. In: Proceedings of the ACM on Human-
Computer Interaction 5.ISS (2021). DOI: 10.1145/3488550. URL: https://hal-enac.archives-
ouvertes.fr/hal-03405986.
<scratchpad>
- Main topic: Inria Centre at the University of Bordeaux's research centre, Potioc, focusing on novel multimodal interactions for a stimulating user experience.
- Key points:
  - Investigating new forms of interaction to push the boundaries of current interactive systems.
  - Exploring approaches that vary the level of materiality (physical vs. virtual) in output and input spaces.
  - Targeting education, art, entertainment, and well-being domains.
  - Developing brain-computer interfaces (BCIs) for motor imagery, physiological computing, and tangible interfaces.
  - Collaborating with experts in Educational Sciences, neuropsychology, and environmental sciences.
  - Focusing on improving the reliability and robustness of BCIs.
- Structure: The document is organized into sections, including the project team, activity report, research program, application domains, social and environmental responsibility, and dissemination.
- Potential artifacts to ignore: Links, HTML tags, and other web-related elements.
</scratchpad>

<final_summary>
The Inria Centre at the University of Bordeaux's research centre, Potioc, focuses on developing novel multimodal interactions for a stimulating user experience. The centre investigates new approaches to push the boundaries of current interactive systems, targeting education, art, entertainment, and well-being domains. Potioc also develops brain-computer interfaces (BCIs) for motor imagery, physiological computing, and tangible interfaces, collaborating with experts in Educational Sciences, neuropsychology, and environmental sciences. The centre aims to improve the reliability and robustness of BCIs, with a focus on improving the user experience and promoting pro-environmental behaviors. Through its research, Potioc seeks to contribute to the emergence of new applications and usages, with a societal impact.
The Inria Centre at the University of Bordeaux's research centre, Potioc, focuses on developing novel multimodal interactions for a stimulating user experience. The centre investigates new approaches to push the boundaries of current interactive systems, targeting education, art, entertainment, and well-being domains. Potioc also develops brain-computer interfaces (BCIs) for motor imagery, physiological computing, and tangible interfaces, collaborating with experts in Educational Sciences, neuropsychology, and environmental sciences. The centre aims to improve the reliability and robustness of BCIs, with a focus on improving the user experience and promoting pro-environmental behaviors. Through its research, Potioc seeks to contribute to the emergence of new applications and usages, with a societal impact.