Advertisement

Detection of Gait Initiation Through a ERD-Based Brain-Computer Interface

  • E. HortalEmail author
  • D. Planelles
  • E. Iáñez
  • A. Costa
  • A. Úbeda
  • J. M. Azorín
Chapter
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 12)

Abstract

In this paper, an experiment designed to detect the will to perform several steps forward (as gait initiation) before it occurs using the electroencephalographic (EEG) signals collected from the scalp is presented. In order to detect this movement intention, the Event-Related Desynchronization phenomenon is detected using a SVM-based classifier. The preliminary results from seven users have been presented. In this work, the results obtained in a previous paper are enhance obtaining similar true positive rates (around 66 % in average) but reducing the false positive rates (with an average around 20 %). In the future, this improved Brain-Computer Interface will be used as part of the control system of an exoskeleton attached to the lower limb of people with incomplete and complete spinal cord injury to initiate their gait cycle.

Keywords

Support Vector Machine Spinal Cord Injury Inertial Measurement Unit Movement Onset Functional Electrical Stimulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research has been funded by the Commission of the European Union under the BioMot project—Smart Wearable Robots with Bioinspired Sensory-Motor Skills (Grant Agreement number IFP7-ICT-2013-10-611695) and by Conselleria d’Educació, Cultura i Esport of Generalitat Valenciana of Spain through grant VALi+d ACIF/2012/135.

References

  1. 1.
    Dornhege, G., Millán, J., del, R., Hinterberger, T., MacFarland, D.J., Muller, K.R.: Towards Brain-Computer Interfacing. The MIT Press (2007)Google Scholar
  2. 2.
    Nicolelis, M.A.L.: Actions from thoughts. Nature 409, 403–407 (2001)CrossRefGoogle Scholar
  3. 3.
    Bai, O., Rathi, V., Lin, P., Huang, D., Battapady, H., Fei, D.Y., Schneider, L., Houdayer, E., Chen, X., Hallett, M.: Prediction of human voluntary movement before it occurs. Clin. Neurophysiol. 122(2), 364–372 (2011)CrossRefGoogle Scholar
  4. 4.
    Moreno, J.C., Ama, A.J., Reyes-Guzmán, A., Gil-Agudo, N., Ceres, R., Pons, J.L.: Neurorobotic and hybrid management of lower limb motor disorders: a review. Med. Biol. Eng. Comput. 49(10), 1119–1130 (2011)CrossRefGoogle Scholar
  5. 5.
    Kolb, B., Muhammad, A., Gibb, R.: Searching for factors underlying cerebral plasticity in the normal and injured brain. J. Commun. Disord. 44, 503–514 (2011)CrossRefGoogle Scholar
  6. 6.
    Shibasaki, H., Hallett, M.: What is the Bereitschaftspotential? Clin. Neurophysiol. 117, 2341–2356 (2006)CrossRefGoogle Scholar
  7. 7.
    Pfurtscheller, G., da Silva, F.H.L.: Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol. 110, 1842–1857 (1999)CrossRefGoogle Scholar
  8. 8.
    Planelles, D., Hortal, E., Costa, A., Iáñez, E., Azorín, J.M.: First steps in the development of an EEG-based system to detect intention of gait initiation. In: 8th Annual IEEE International Systems Conference, Ottawa, Canada, pp. 167–171 (2014)Google Scholar
  9. 9.
    McFarland, D.J., McCane, L.M., David, S.V., Wolpaw, J.R.: Spatial filter selection for EEG-based communication. Electroencephalogr. Clin. Neurophysiol. 103, 386–394 (1999)CrossRefGoogle Scholar
  10. 10.
    Bracewell, R.N.: The Fourier Transform and Its Applications. McGraw-Hill Electrical and Electronic Engineering Series (1978)Google Scholar
  11. 11.
    Hsu, C.W., Chang, C.C., Lin, C.J.: A practical guide to support vector classification. http://www.csie.ntu.edu.tw/cjlin/libsvm/
  12. 12.
    Wei, L., Yue, H., Jiang, X., He, J.: Brain activity during walking in patient with spinal cord injury. In: International Symposium on Bioelectronics and Bioinformatics, pp. 96–99 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • E. Hortal
    • 1
    Email author
  • D. Planelles
    • 1
  • E. Iáñez
    • 1
  • A. Costa
    • 1
  • A. Úbeda
    • 1
  • J. M. Azorín
    • 1
  1. 1.Brain-Machine Interface Systems LabMiguel Hernández University of ElcheElche (Alicante)Spain

Personalised recommendations