Camille Jeunet
Camille Jeunet
CNRS Researcher, CLLE Lab (UT2, CNRS), TMBI (Univ. Toulouse)
Verified email at - Homepage
Cited by
Cited by
EEG-based workload estimation across affective contexts
C Mühl, C Jeunet, F Lotte
Frontiers in neuroscience 8, 114, 2014
Why standard brain-computer interface (BCI) training protocols should be changed: an experimental study
C Jeunet, E Jahanpour, F Lotte
Journal of neural engineering 13 (3), 036024, 2016
Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns
C Jeunet, B N'Kaoua, S Subramanian, M Hachet, F Lotte
PLoS ONE 10 (12), e0143962, 2015
Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)
T Ros, S Enriquez-Geppert, V Zotev, KD Young, G Wood, ...
Brain 143 (6), 1674-1685, 2020
Advances in user-training for mental-imagery-based BCI control: Psychological and cognitive factors and their neural correlates
C Jeunet, B N’Kaoua, F Lotte
Progress in brain research 228, 3-35, 2016
Towards improved BCI based on human learning principles
F Lotte, C Jeunet
The 3rd International Winter Conference on Brain-Computer Interface, 1-4, 2015
Continuous tactile feedback for motor-imagery based brain-computer interaction in a multitasking context
C Jeunet, C Vi, D Spelmezan, B N’Kaoua, F Lotte, S Subramanian
IFIP Conference on Human-Computer Interaction, 488-505, 2015
Towards BCI-based interfaces for augmented reality: feasibility, design and evaluation
H Si-Mohammed, J Petit, C Jeunet, F Argelaguet, F Spindler, A Evain, ...
IEEE transactions on visualization and computer graphics 26 (3), 1608-1621, 2018
“Do you feel in control?”: towards novel approaches to characterise, manipulate and measure the sense of agency in virtual environments
C Jeunet, L Albert, F Argelaguet, A Lécuyer
IEEE transactions on visualization and computer graphics 24 (4), 1486-1495, 2018
Using recent BCI literature to deepen our understanding of clinical neurofeedback: a short review
C Jeunet, F Lotte, JM Batail, P Philip, JAM Franchi
Neuroscience 378, 225-233, 2018
Defining and quantifying users’ mental imagery-based BCI skills: a first step
F Lotte, C Jeunet
Journal of neural engineering 15 (4), 046030, 2018
Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects
C Jeunet, B Glize, A McGonigal, JM Batail, JA Micoulaud-Franchi
Neurophysiologie Clinique 49 (2), 125-136, 2019
Towards explanatory feedback for user training in brain-computer interfaces
J Schumacher, C Jeunet, F Lotte
2015 IEEE International Conference on Systems, Man, and Cybernetics, 3169-3174, 2015
EEG neurofeedback research: A fertile ground for psychiatry?
JM Batail, S Bioulac, F Cabestaing, C Daudet, D Drapier, M Fouillen, ...
L'encephale 45 (3), 245-255, 2019
How Well Can We Learn With Standard BCI Training Approaches? A Pilot Study.
C Jeunet, A Cellard, S Subramanian, M Hachet, B N'Kaoua, F Lotte
6th International Brain-Computer Interface Conference, 2014
Towards a cognitive model of MI-BCI user training
C Jeunet, B N'Kaoua, F Lotte
International Graz BCI Conference, 2017
Online classification accuracy is a poor metric to study mental imagery-based BCI user learning: an experimental demonstration and new metrics
F Lotte, C Jeunet
7th international BCI conference, 2017
Towards a spatial ability training to improve Mental Imagery based Brain-Computer Interface (MI-BCI) performance: A Pilot study
S Teillet, F Lotte, B N'Kaoua, C Jeunet
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016
A review of user training methods in brain computer interfaces based on mental tasks
A Roc, L Pillette, J Mladenovic, C Benaroch, B N'Kaoua, C Jeunet, F Lotte
Journal of Neural Engineering, 2020
Mind the traps! Design guidelines for rigorous BCI experiments
C Jeunet, S Debener, F Lotte, J Mattout, R Scherer, C Zich
Brain–Computer Interfaces Handbook: Technological and Theoretical Advances, 1-33, 2018
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