TOWARD DOMOTIC APPLIANCES CONTROL THROUGH A SELF-PACED P300-BASED BCI

F. Aloise, F. Schettini, P. Aricò, F. Leotta, S. Salinari, D. Mattia, F. Babiloni, F. Cincotti

2011

Abstract

During recent years there has been a growing interest in Brain Computer Interface (BCI) systems as an alternative means of interaction with the external world for people with severe motor disabilities. The use of the P300 event-related potentials as control feature allows users to choose between various options (letters or icons) requiring a very short calibration phase. The aim of this work is to improve performances and flexibility of P300 based BCIs. An efficient BCI system should be able to understand user's intentions from the ongoing EEG, abstaining from doing a selection when the user is engaged in a different activity, and changing its speed of selection depending on current user's attention level. Our self-paced system addresses all these issues representing an important step beyond the classical synchronous P300 BCI that forces the user in a continuous control task. Experimentation has been performed on 10 healthy volunteers acting on a BCI-controlled domestic environment in order to demonstrate the potential usability of BCI systems in everyday life. Results show that the self-paced BCI increases information transfer rate with respect to the synchronous one, being very robust, at the same time, in avoiding false negatives when the user is not engaged in a control task.

References

  1. Cincotti, F. et al., 2008. Non-invasive brain-computer interface system: towards its application as assistive technology. Brain Research Bulletin, 75(6), 796-803.
  2. Draper, N. R. & Smith, H., 1998. Applied Regression Analysis Third., Wiley-Interscience.
  3. Fabiani, M. et al., 1987. Definition, identification and reliability of measurement of the P300 component of the event-related brain potential. , 2, 1-78.
  4. Farwell, L. A. & Donchin, E., 1988. Talking off the top of your head: toward a mental prosthesis utilizing eventrelated brain potentials. Electroencephalography and Clinical Neurophysiology, 70(6), 510-523.
  5. Fisher, R. A., 1936. The Use of Multiple Measurements in Taxonomic Problems. [[Annals of Eugenics]], 7, 179- 188.
  6. Krusienski, D. J. et al., 2008. Toward enhanced P300 speller performance. Journal of Neuroscience Methods, 167(1), 15-21.
  7. Krusienski, D. J. et al., 2006. A comparison of classification techniques for the P300 Speller. Journal of Neural Engineering, 3(4), 299-305.
  8. Mason, S. G. & Birch, G. E., 2000. A brain-controlled switch for asynchronous control applications. IEEE Transactions on Bio-Medical Engineering, 47(10), 1297-1307.
  9. Millán, J. D. R. & Mouriño, J., 2003. Asynchronous BCI and local neural classifiers: an overview of the Adaptive Brain Interface project. IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of the IEEE Engineering in Medicine and Biology Society, 11(2), 159-161.
  10. Polich, J. & Kok, A., 1995. Cognitive and biological determinants of P300: an integrative review. Biological Psychology, 41(2), 103-146.
  11. Schalk, G. et al., 2004. BCI2000: a general-purpose braincomputer interface (BCI) system. IEEE Transactions on Bio-Medical Engineering, 51(6), 1034-1043.
  12. Townsend, G., Graimann, B. & Pfurtscheller, G., 2004. Continuous EEG classification during motor imagery-- simulation of an asynchronous BCI. IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of the IEEE Engineering in Medicine and Biology Society, 12(2), 258-265.
  13. Wolpaw, J. R. et al., 2002. Brain-computer interfaces for communication and control. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 113(6), 767- 91.
  14. Wolpaw, J. R. & McFarland, D. J., 2004. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences of the United States of America, 101(51), 17849-17854.
  15. Zhang, H., Guan, C. & Wang, C., 2008. Asynchronous P300-based brain-computer interfaces: a computational approach with statistical models. IEEE Transactions on Bio-Medical Engineering, 55(6), 1754-1763.
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Paper Citation


in Harvard Style

Aloise F., Schettini F., Aricò P., Leotta F., Salinari S., Mattia D., Babiloni F. and Cincotti F. (2011). TOWARD DOMOTIC APPLIANCES CONTROL THROUGH A SELF-PACED P300-BASED BCI . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 239-244. DOI: 10.5220/0003162002390244


in Bibtex Style

@conference{biosignals11,
author={F. Aloise and F. Schettini and P. Aricò and F. Leotta and S. Salinari and D. Mattia and F. Babiloni and F. Cincotti},
title={TOWARD DOMOTIC APPLIANCES CONTROL THROUGH A SELF-PACED P300-BASED BCI},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={239-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003162002390244},
isbn={978-989-8425-35-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - TOWARD DOMOTIC APPLIANCES CONTROL THROUGH A SELF-PACED P300-BASED BCI
SN - 978-989-8425-35-5
AU - Aloise F.
AU - Schettini F.
AU - Aricò P.
AU - Leotta F.
AU - Salinari S.
AU - Mattia D.
AU - Babiloni F.
AU - Cincotti F.
PY - 2011
SP - 239
EP - 244
DO - 10.5220/0003162002390244