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    Camille Jeunet

    Camille Jeunet obtained a M.Sc (2013) as well as a PhD (2016) degree in cognitive sciences, both from the University of Bordeaux. Her PhD was awarded by the European Label and by 3 PhD awards, from IFRATH-Kaelis (best PhD in assistive technologies), from the IEEE SMC society (best PhD in Human-Computer Interaction) and from the University of Bordeaux (special prize of the international committee). In 2017-2018, she was hired for a post-doc at EPFL (Geneva, Switzerland) and Inria (Rennes, France). Since October 2018, she has been a Research Scientist at CNRS (the french National Center for Scientific Research) in the CLLE Lab, Toulouse, France. She leads an interdisciplinary research bringing together computer science, psychology and neurosciences in order to better understand the processes underlying human learning in Brain-Computer Interfaces (BCIs), and improve BCI user-training. She is particularly interested in using these technologies to improve motor skills in athletes and in patients who suffered from a stroke. Since 2017, she has been part of the board of the BCI french association, called CORTICO. She is notably in charge of organising, each year, the meeting of this association as well as a conference for the young researchers of the domain.

    Journal articles11 documents

    • Jean-Marie Batail, Stéphanie Bioulac, François Cabestaing, C. Daudet, Dominique Drapier, et al.. EEG neurofeedback research A fertile ground for psychiatry?. L'Encéphale, Elsevier Masson, 2019, 45 (3), pp.245-255. ⟨10.1016/j.encep.2019.02.001⟩. ⟨hal-02094863⟩
    • Camille Jeunet, Fabien Lotte, Jean-Arthur Micoulaud-Franchi. Modélisation des processus cognitifs et neurophysiologiques sous-tendant l’apprentissage neurofeedback : le rôle de l’attention. Neurophysiologie Clinique/Clinical Neurophysiology, Elsevier Masson, 2019, 49 (3), pp.198. ⟨⟩. ⟨10.1016/j.neucli.2019.05.048⟩. ⟨hal-02167229⟩
    • Camille Jeunet, Louis Albert, Ferran Argelaguet Sanz, Anatole Lécuyer. " Do you feel in control? " : Towards Novel Approaches to Characterise, Manipulate and Measure the Sense of Agency in Virtual Environments. IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2018, 24 (4), pp.1486-1495. ⟨10.1109/TVCG.2018.2794598⟩. ⟨hal-01679143v2⟩
    • Hakim Si-Mohammed, Jimmy Petit, Camille Jeunet, Ferran Argelaguet Sanz, Fabien Spindler, et al.. Towards BCI-based Interfaces for Augmented Reality: Feasibility, Design and Evaluation. IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2018, pp.1-12. ⟨10.1109/TVCG.2018.2873737⟩. ⟨hal-01947344⟩
    • Fabien Lotte, Camille Jeunet. Defining and Quantifying Users' Mental Imagery-based BCI skills: a first step. Journal of Neural Engineering, IOP Publishing, 2018, 15 (4), pp.1-37. ⟨10.1088/1741-2552/aac577⟩. ⟨hal-01846434⟩
    • Camille Jeunet, Fabien Lotte, Jean-Marie Batail, Pierre Philip, Jean-Arthur Micoulaud-Franchi. Using recent BCI literature to deepen our understanding of clinical neurofeedback: A short review. Neuroscience, Elsevier - International Brain Research Organization, 2018, 378, pp.225-233. ⟨10.1016/j.neuroscience.2018.03.013⟩. ⟨hal-01728767⟩
    • Camille Jeunet, Bertrand Glize, Aileen Mcgonigal, Jean-Marie Batail, Jean-Arthur Micoulaud-Franchi. Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects. Neurophysiologie Clinique/Clinical Neurophysiology, Elsevier Masson, In press, 49 (2), pp.125-136. ⟨10.1016/j.neucli.2018.10.068⟩. ⟨hal-01919018⟩
    • Camille Jeunet, Emilie Jahanpour, Fabien Lotte. Why Standard Brain-Computer Interface (BCI) Training Protocols Should be Changed: An Experimental Study. Journal of Neural Engineering, IOP Publishing, 2016. ⟨hal-01302154⟩
    • Camille Jeunet, Bernard N'Kaoua, Fabien Lotte. Advances in User-Training for Mental-Imagery Based BCI Control: Psychological and Cognitive Factors and their Neural Correlates. Progress in brain research, Elsevier, 2016. ⟨hal-01302138v2⟩
    • Camille Jeunet, Bernard N'Kaoua, Sriram Subramanian, Martin Hachet, Fabien Lotte. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns. PLoS ONE, Public Library of Science, 2015, 10 (12), pp.23. ⟨10.1371/journal.pone.0143962⟩. ⟨hal-01177685v2⟩
    • Christian Mühl, Camille Jeunet, Fabien Lotte. EEG-based workload estimation across affective contexts. Frontiers in Neuroscience, Frontiers, 2014, 8 (114). ⟨hal-01006511⟩

    Conference papers14 documents

    • Camille Benaroch, Camille Jeunet, Fabien Lotte. Are users' traits informative enough to predict/explain their mental-imagery based BCI performances ?. 8th Graz BCI Conference 2019, Sep 2019, Graz, Austria. ⟨hal-02111581⟩
    • Léa Pillette, Camille Jeunet, Roger N'Kambou, Bernard N'Kaoua, Fabien Lotte. Towards Artificial Learning Companions for Mental Imagery-based Brain-Computer Interfaces. WACAI 2018 - Workshop sur les “Affects, Compagnons Artificiels et Interactions”, Jun 2018, Ile de Porquerolles, France. pp.1-8. ⟨hal-01762612v2⟩
    • Camille Jeunet, Bernard N'Kaoua, Fabien Lotte. Towards a cognitive model of MI-BCI user training . International Graz BCI Conference , Sep 2017, Graz, Austria. ⟨hal-01519476⟩
    • Fabien Lotte, Camille Jeunet. Online classification accuracy is a poor metric to study mental imagery-based bci user learning: an experimental demonstration and new metrics . 7th International BCI Conference, Sep 2017, Graz, Austria. ⟨hal-01519478⟩
    • Camille Jeunet, Benoit Bideau, Ferran Argelaguet Sanz, Ricardo Chavarriaga, José Del R. Millán, et al.. Investigating neurophysiological correlates of covert attention in soccer goalkeepers. WCSS 2017 - World Conference on Science and Soccer, May 2017, Rennes, France. pp.1. ⟨hal-01669331⟩
    • Léa Pillette, Camille Jeunet, Boris Mansencal, Roger N 'Kambou, Bernard N 'Kaoua, et al.. PEANUT: Personalised Emotional Agent for Neurotechnology User-Training. 7th International BCI Conference, Sep 2017, Graz, Austria. ⟨hal-01519480⟩
    • Suzy Teillet, Fabien Lotte, Bernard N'Kaoua, Camille Jeunet. Towards a Spatial Ability Training to Improve Mental Imagery based Brain-Computer Interface (MI-BCI) Performance: a Pilot Study. IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016) , Oct 2016, Budapest, Hungary. pp.6. ⟨hal-01341042⟩
    • Camille Jeunet. Training Users' Spatial Abilities to Improve Brain-Computer Interface Performance: A Theoretical Approach. 9th Conference of Young Researchers in Cognitives Sciences, Jun 2015, Paris, France. ⟨hal-01162411⟩
    • Camille Jeunet, Bernard N'Kaoua, Martin Hachet, Fabien Lotte. Predicting Mental-Imagery Based Brain-Computer Interface Performance from Psychometric Questionnaires. womENcourage, Sep 2015, Uppsala, Sweden. ⟨hal-01162415⟩
    • Julia Schumacher, Camille Jeunet, Fabien Lotte. Towards Explanatory Feedback for User Training in Brain–Computer Interfaces. IEEE International Conference on Systems Man & Cybernetics (IEEE SMC), Oct 2015, Hong-Kong, China. ⟨hal-01179329⟩
    • Fabien Lotte, Camille Jeunet. Towards Improved BCI based on Human Learning Principles. 3rd International Winter Conference on Brain-Computer Interfaces, Jan 2015, High1 Resort, South Korea. ⟨hal-01111843⟩
    • Camille Jeunet, Chi Vi, Daniel Spelmezan, Bernard N'Kaoua, Fabien Lotte, et al.. Continuous Tactile Feedback for Motor-Imagery based Brain-Computer Interaction in a Multitasking Context. 15th Human-Computer Interaction (INTERACT), Sep 2015, Bamberg, Germany. pp.488-505, ⟨10.1007/978-3-319-22701-6_36⟩. ⟨hal-01159146⟩
    • Camille Jeunet, Alison Cellard, Sriram Subramanian, Martin Hachet, Bernard N'Kaoua, et al.. How Well Can We Learn With Standard BCI Training Approaches? A Pilot Study.. 6th International Brain-Computer Interface Conference, Sep 2014, Graz, Austria. ⟨hal-01052692⟩
    • Camille Jeunet, Christian Mühl, Fabien Lotte. Design and Validation of a Mental and Social Stress Induction Protocol Towards Load-Invariant Physiology-Based Detection. International Conference on Physiological Computing Systems, Jan 2014, Lisbonne, Portugal. ⟨hal-00879966⟩

    Poster communications6 documents

    • Léa Pillette, Bertrand Glize, Bernard N'Kaoua, Pierre-Alain Joseph, Camille Jeunet, et al.. Impact of MI-BCI feedback for post-stroke and neurotypical people. Journée Jeunes Chercheurs en Interfaces Cerveau-Ordinateur et Neurofeedback (JJC-ICON’2019), Mar 2019, Lille, France. ⟨hal-02095124⟩
    • Camille Benaroch, Camille Jeunet, Fabien Lotte. Using computational modelling to better understand and predict Mental-Imagery based BCI (MI-BCI) users' performance. Journées CORTICO 2018 - COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur, Apr 2018, Toulouse, France. ⟨hal-01847280⟩
    • Camille Jeunet, Fabien Lotte, Martin Hachet, Sriram Subramanian, Bernard N'Kaoua. Spatial Abilities Play a Major Role in BCI Performance. 6th International BCI Meeting, May 2016, Asilomar, United States. 2016. ⟨hal-01285369⟩
    • Camille Jeunet, Bernard N'Kaoua, Roger N'Kambou, Fabien Lotte. Why and How to Use Intelligent Tutoring Systems to Adapt MI-BCI Training to Each User. 6th International BCI Meeting, May 2016, Asilomar, United States. 2016. ⟨hal-01285365⟩
    • Camille Jeunet, Fabien Lotte, Martin Hachet, Bernard N'Kaoua. Impact of Cognitive And Personality Profiles On Motor-Imagery Based Brain-Computer Interface-Controlling Performance. 17th World Congress of Psychophysiology (IOP2014), Sep 2014, Hiroshima, Japan. ⟨hal-01088811v2⟩
    • Camille Jeunet, Christian Mühl, Fabien Lotte. Conception et validation d'un protocole pour induire du stress et le mesurer dans des signaux physiologiques. 25ème conférence francophone sur l'Interaction Homme-Machine, IHM'13, Nov 2013, Bordeaux, France. ⟨hal-00879588⟩

    Book sections3 documents

    • Fabien Lotte, Camille Jeunet, Jelena Mladenović, Bernard N'Kaoua, Léa Pillette. A BCI challenge for the signal processing community: considering the user in the loop. Signal Processing and Machine Learning for Brain-Machine Interfaces, IET, pp.1-33, 2018, 978-1-78561-398-2. ⟨⟩. ⟨hal-01762573v2⟩
    • Camille Jeunet, Stefan Debener, Fabien Lotte, Jeremie Mattout, Reinhold Scherer, et al.. Mind the Traps! Design Guidelines for Rigorous BCI Experiments. Chang S. Nam; Anton Nijholt; Fabien Lotte. Brain–Computer Interfaces Handbook: Technological and Theoretical Advances, CRC Press pp.1-33, 2018, 9781498773430. ⟨hal-01620186⟩
    • Camille Jeunet, Fabien Lotte, Bernard N'Kaoua. Apprentissage humain pour les interfaces cerveau-ordinateur. Wiley; ISTE. Les Interfaces Cerveau-Ordinateur , 1, 2016, Fondements & Méthodes. ⟨hal-01414106⟩

    Other publications1 document

    • Anke Brock, Camille Jeunet. Nouvelles technologies et handicap. 2019, ⟨hal-02092400⟩

    Theses1 document

    • Camille Jeunet. Understanding & Improving Mental-Imagery Based Brain-Computer Interface (Mi-Bci) User-Training : towards A New Generation Of Reliable, Efficient & Accessible Brain- Computer Interfaces. Psychology. Université de Bordeaux, 2016. English. ⟨NNT : 2016BORD0221⟩. ⟨tel-01417606⟩

    Lectures1 document

    • Jérémy Frey, Camille Jeunet, Jelena Mladenovic, Léa Pillette, Fabien Lotte. When HCI Meets Neurotechnologies: What You Should Know about Brain-Computer Interfaces. 3rd cycle. ACM Conference on Human Factors in Computing Systems (CHI 2017), Denver, United States. 2017. ⟨cel-01418705⟩