Search

Your search keyword '"Popular interaction with 3d content (Potioc)"' showing total 3 results
Start Over Author "Popular interaction with 3d content (Potioc)" Publisher frontiers media s.a.
3 results on '"Popular interaction with 3d content (Potioc)"'

1. Detection and Estimation of Working Memory States and Cognitive Functions Based on Neurophysiological Measures

Author

Christian Mühl, Fabien Lotte, Christian Herff, Felix Putze, Stephen H. Fairclough, University of Bremen, German Aerospace Center (DLR), Popular interaction with 3d content (Potioc), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Liverpool John Moores University (LJMU), Maastricht University [Maastricht], RS: MHeNs - R3 - Neuroscience, Neurochirurgie, and Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest

Subjects
cognitive functions, Computer science, Electroencephalography, lcsh:RC321-571, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, BCI (brain computer interface), [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, medicine, 0501 psychology and cognitive sciences, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], EEG, Bci brain computer interface, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, ComputingMilieux_MISCELLANEOUS, 050107 human factors, Biological Psychiatry, working memory - long-term memory interactions, Estimation, medicine.diagnostic_test, Working memory, [SCCO.NEUR]Cognitive science/Neuroscience, 05 social sciences, Cognition, General Medicine, Neurophysiology, Psychiatry and Mental health, Neuropsychology and Physiological Psychology, Editorial, Neurology, Working memory-long-term memory interactions, fNIRS (functional near infrared spectroscopy), [SCCO.PSYC]Cognitive science/Psychology, 030217 neurology & neurosurgery, cognitive processes, Cognitive psychology, Neuroscience
Abstract

International audience

Published
2018
Full Text
View/download PDF

2. Making Tangible the Intangible: Hybridization of the Real and the Virtual to Enhance Learning of Abstract Phenomena

Author

Stéphanie Fleck, Martin Hachet, Psychologie Ergonomique et Sociale pour l'Expérience utilisateurs (PErSEUs), Université de Lorraine (UL), Popular interaction with 3d content (Potioc), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest

Subjects
Computer Networks and Communications, Computer science, [SHS.EDU]Humanities and Social Sciences/Education, Context (language use), instructional design, 02 engineering and technology, computer.software_genre, Field (computer science), lcsh:QA75.5-76.95, tangible interaction, Artificial Intelligence, Human–computer interaction, human-computer interaction, human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, Leverage (statistics), [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], ComputingMilieux_MISCELLANEOUS, education, Multimedia, Instructional design, 05 social sciences, 050301 education, 020207 software engineering, augmented reality, Hardware and Architecture, ICT, Augmented reality, lcsh:Electronic computers. Computer science, User interface, 0503 education, computer, Software, Information Systems
Abstract

Interactive systems based on Augmented Reality (AR) and Tangible User Interfaces (TUI) hold great promise for enhancing the learning and understanding of abstract phenomena. In particular, they enable to take advantage of numerical simulation and pedagogical supports, while keeping the learner involved in true physical experimentations. In this paper, we present three examples based on AR and TUI, where the concepts to be learnt are difficult to perceive. The first one, Helios, targets K-12 learners in the field of astronomy. The second one, Hobit is dedicated to experiments in wave optics. Finally, the third one, Teegi, allows one to get to know more about brain activity. These three hybrid interfaces have emerged from a common basis that jointly combines research and development work in the fields of Instructional Design and Human-Computer Interaction, from theoretical to practical aspects. On the basis of investigations carried out in real context of use and on the grounding works in education and HCI which corroborate the design choices that were made, we formalize how and why the hybridization of the real and the virtual enables to leverage the way learners understand intangible phenomena in Sciences education.

Published
2016
Full Text
View/download PDF

3. Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design

Author

Fabien Lotte, Christian Mühl, Florian Larrue, Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), Popular interaction with 3d content (Potioc), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), and Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest

Subjects
[SDV.BIO]Life Sciences [q-bio]/Biotechnology, Brain-Computer Interface, Computer science, [SHS.EDU]Humanities and Social Sciences/Education, Control (management), [SCCO.COMP]Cognitive science/Computer science, training protocols, instructional design, feedback, Training approach, 050105 experimental psychology, lcsh:RC321-571, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, InformationSystems_MODELSANDPRINCIPLES, motivation, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Robustness (computer science), Human–computer interaction, Human-in-the-loop, 0501 psychology and cognitive sciences, EEG, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], BCI, [INFO.INFO-BT]Computer Science [cs]/Biotechnology, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, Brain–computer interface, Signal processing, business.industry, Instructional design, 05 social sciences, brain-computer interface (BCI), Hypothesis and Theory Article, Psychiatry and Mental health, Neuropsychology and Physiological Psychology, Neurology, Brain-Computer Interfaces, [SCCO.PSYC]Cognitive science/Psychology, Key (cryptography), [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, Artificial intelligence, business, 030217 neurology & neurosurgery, electroencephalography, Mental image, Neuroscience
Abstract

International audience; While recent research on Brain-Computer Interfaces (BCI) has highlighted their potential for many applications, they remain barely used outside laboratories. The main reason is their lack of robustness. Indeed, with current BCI, mental state recognition is usually slow and often incorrect. Spontaneous BCI (i.e., mental imagery-based BCI) often rely on mutual learning efforts by the user and the machine, with BCI users learning to produce stable ElectroEncephaloGraphy (EEG) patterns (spontaneous BCI control being widely acknowledged as a skill) while the computer learns to automatically recognize these EEG patterns, using signal processing. Most research so far was focused on signal processing, mostly neglecting the human in the loop. However, how well the user masters the BCI skill is also a key element explaining BCI robustness. Indeed, if the user is not able to produce stable and distinct EEG patterns, then no signal processing algorithm would be able to recognize them. Unfortunately, despite the importance of BCI training protocols, they have been scarcely studied so far, and used mostly unchanged for years. In this paper, we advocate that current human training approaches for spontaneous BCI are most likely inappropriate. We notably study instructional design literature in order to identify the key requirements and guidelines for a successful training procedure that promotes a good and efficient skill learning. This literature study highlights that current spontaneous BCI user training procedures satisfy very few of these requirements and hence are likely to be suboptimal. We therefore identify the flaws in BCI training protocols according to instructional design principles, at several levels: in the instructions provided to the user, in the tasks he/she has to perform, and in the feedback provided. For each level, we propose new research directions that are theoretically expected to address some of these flaws and to help users learn the BCI skill more efficiently.

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results