IMMERSIVE NEUROFEEDBACK - A New Paradigm

Mohamed Elgendi, Francois Vialatte, Martin Constable, Justin Dauwels

2011

Abstract

Healthcare organizations continue to pursue ways of offering higher-quality care to face the demand and expectations in promoting and maintaining health and in disease prevention. Currently, in neuroscience, there is an undergoing paradigm shift towards immersive neurofeedback mechanism. This will improve the user’s (or patient’s) ability to control brain activity, medical diagnoses, and rehabilitation of neurological or psychiatric disorders. Indeed, several psychological and medical studies have confirmed that virtual immersive activity is enjoyable, stimulating, and can have a healing effect. The new paradigm consists of an immersive room and three input devices: Emotiv headset (wireless non-invasive acquisition of brain waves), Kinect camera (gesture recognition), and wireless microphone (voice/speech recognition); towards immersive treatment and better quality health system in the near future.

References

  1. Journal of Clinical Neurophysiology 8(2) pp. 200-202.
  2. AutoNOMOS project Freie Universität Berlin. (2011).
  3. Brain Driver. [online] Available at: <http:// autonomos.inf.fu-berlin.de/news/brain-driver> [Accessed 10 May 2011] Babiloni, F., Cincotti, F., Bianchi, L., Pirri, G., Millán, J.
  4. R., Mourio, J., Salinari, S. and Marciani, M.G. (2001).
  5. Medical Engineering Samp; Physics 23, pp. 323-328.
  6. E. (2007). A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals. Journal of Neural Engineering, 4(2), R32-57.
  7. Bayliss, J. D. (2003). Use of the evoked potential P3 component for control in a virtual environment. IEEE Transactions on Neural Systems and Rehabilitation Engineering 11, pp. 113-116.
  8. Campbell, A. T., Choudhury, T., Hu, S., Lu, H., Mukerjee, M. K., Rabbi, M. and Raizada, R. D. S. (2010).
  9. NeuroPhone: Brain-Mobile Phone Interface using a Wireless EEG Headset. [online] Available at <http://sensorlab.cs.dartmouth.edu/publications.html> [Accessed 15 May 2011] Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G, Henriquez, C. S. and Nicolelis, M. A. L. (2003).
  10. Learning to control a brain-machine interface for reaching and grasping by primates. PloS Biology 1, pp.
  11. Farland, D. J. and Müller, K.-R. (2007). Towards BrainComputer Interfacing, MIT Press, Cambridge, Massachussets.
  12. J. and Millán, J. R. (2008). A brainactuated wheelchair: Asynchronous and non-invasive Brain-computer interfaces for continuous control of robots. Clinical Neurophysiology 119, pp. 2159-2169.
  13. Garrett, D., Peterson, D. A., Anderson, C. W. and Thaut, M. H. (2003). Comparison of Linear and Nonlinear Methods for EEG Signal Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol 11 (2), pp. 141-144.
  14. Guger, C., Schlögl, A., Neuper, C., Walterspacher, D., Strein, T. and Pfurtscheller, G. (2001). Rapid Prototyping of an EEG-Based Brain-Computer Interface (BCI). IEEE Transactions on Rehabilitation Engineering, vol. 9(1), pp. 49-58.
  15. Guger, C., Holzner, C., Grönegress, C., Edlinger, G. and Slater, M. (2008). Control of a smart home with a Brain-Computer Interface. 4th International BrainComputer Interface Workshop and Training Course 2008, Graz, Austria.
  16. Hsu, C.-W., Chang, C.-C. and Lin, C.-J. (2003). A Practical Guide to Support Vector Classification.
  17. Serruya, M. D., Harsopoulos, N. G., Paninski, L., Fellows, M. R. and Donoghue, K. (2002). Instant neural control of a movement signal. Nature 416, pp. 141-142.
  18. Sirvent, J. L., Azorín, J. M., Iáñez, E., Úbeda, A. and Fernández, E. (2010). P300-based BCI for Internet browsing. 8th International Conference on Practical Applications of Agents and Multiagent Systems, IEEE Spanish Chapter. Trends in PAAMS, AISC 71, pp.
  19. Clinical Neurophysiology 113, pp. 767-791.
Download


Paper Citation


in Harvard Style

Elgendi M., Vialatte F., Constable M. and Dauwels J. (2011). IMMERSIVE NEUROFEEDBACK - A New Paradigm . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: Special Session on Challenges in Neuroengineering, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 465-469. DOI: 10.5220/0003725704650469


in Bibtex Style

@conference{special session on challenges in neuroengineering11,
author={Mohamed Elgendi and Francois Vialatte and Martin Constable and Justin Dauwels},
title={IMMERSIVE NEUROFEEDBACK - A New Paradigm},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: Special Session on Challenges in Neuroengineering, (IJCCI 2011)},
year={2011},
pages={465-469},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003725704650469},
isbn={978-989-8425-84-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: Special Session on Challenges in Neuroengineering, (IJCCI 2011)
TI - IMMERSIVE NEUROFEEDBACK - A New Paradigm
SN - 978-989-8425-84-3
AU - Elgendi M.
AU - Vialatte F.
AU - Constable M.
AU - Dauwels J.
PY - 2011
SP - 465
EP - 469
DO - 10.5220/0003725704650469