The Community for Technology Leaders
RSS Icon
Issue No.05 - Sept.-Oct. (2013 vol.33)
pp: 18-23
Anatole Lecuyer , Inria Rennes
Laurent George , Inria Rennes
Maud Marchal , INSA Rennes
The next generation of VR simulators could take into account a novel input: the user's mental state, as measured with electrodes and a brain-computer interface. One illustration of this promising path is a project that adapted a guidance system's force feedback to the user's mental workload in real time. A first application of this approach is a medical training simulator that provides virtual assistance that adapts to the trainee's mental activity. Such results pave the way to VR systems that will automatically reconfigure and adapt to their users' mental states and cognitive processes.
Haptic interfaces, Electroencephalography, Brain modeling, Visualization, Three-dimensional displays,spatial interfaces, virtual reality, virtual environments, visual interfaces, haptic interfaces, brain-computer interfaces, computer graphics, electroencephalography
Anatole Lecuyer, Laurent George, Maud Marchal, "Toward Adaptive VR Simulators Combining Visual, Haptic, and Brain-Computer Interfaces", IEEE Computer Graphics and Applications, vol.33, no. 5, pp. 18-23, Sept.-Oct. 2013, doi:10.1109/MCG.2013.80
1. J.D. Bayliss, “The Use of the P3 Evoked Potential Component for Control in a Virtual Apartment,” IEEE Trans. Neural Systems and Rehabilitation Eng., vol. 11, no. 2, 2003, pp. 113-116.
2. A. Lécuyer et al., “Brain-Computer Interfaces, Virtual Reality, and Videogames,” Computer, vol. 41, no. 10, 2008, pp. 66-72.
3. F. Lotte et al., “A Review of Classification Algorithms for EEG-Based Brain-Computer Interfaces,” J. Neural Eng., vol. 4, no. 2, 2007.
4. F. Lotte et al., “Exploring Large Virtual Environments by Thoughts Using a Brain-Computer Interface Based on Motor Imagery and High-Level Commands,” Presence, vol. 19, no. 1, 2010, pp. 54-70.
5. J. Legény, R. Viciana-Abad, and A. Lécuyer, “Toward Contextual SSVEP-Based BCI Controller: Smart Activation of Stimuli and Control Weighting,” IEEE Trans. Computational Intelligence and AI in Games, vol. 5, no. 2, 2013, pp. 111-116.
6. L. George et al., “Using Scalp Electrical Biosignals to Control an Object by Concentration and Relaxation Tasks: Design and Evaluation,” Proc. 2011 Int’l Conf. IEEE Eng. in Medicine & Biology Soc. (EMBC 11), IEEE, 2011, pp. 6299-6302.
7. L. George and A. Lécuyer, “An Overview of Research on Passive BCI for Implicit Human-Computer Interaction,” Proc. 1st Int’l Conf. Applied Bionics and Biomechanics (ICABB 10), 2010;
8. F. Lotte et al., “Combining BCI with Virtual Reality: Towards New Applications and Improved BCI,” Towards Practical Brain-Computer Interfaces, B. Allison et al., eds., Springer, 2013, pp. 197-220.
9. D. Friedman et al., “Navigating Virtual Reality by Thought: What Is It Like?,” Presence, vol. 16, no. 1, 2007, pp. 100-110.
10. T.O., Zander and C. Kothe, “Towards Passive Brain-Computer Interfaces: Applying Brain-Computer Interface Technology to Human-Machine Systems in General,” J. Neural Eng., vol. 8, no. 2, 2011.
11. F.M. Stanney et al., “Augmented Cognition: An Overview,” Reviews of Human Factors and Ergonomics, vol. 5, no. 1, 2009, pp. 195-224.
12. C. Mühl et al., “Bacteria Hunt,” J. Multimodal User Interfaces, vol. 4, no. 1, 2010, pp. 11-25.
13. A. Nijholt, D. Plass-Oude Bos, and B. Reuderink, “Turning Shortcomings into Challenges: Brain-Computer Interfaces for Games,” Entertainment Computing, vol. 1, no. 2, 2009, pp. 85-94.
14. L. George et al., “Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance,” Haptics: Perception, Devices, Mobility, and Communication, LNCS 7282, Springer, 2012, pp. 124-135.
100 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool