Advertisement

Human Computer Confluence in BCI for Stroke Rehabilitation

  • Rupert Ortner
  • Danut-Constantin Irimia
  • Christoph Guger
  • Günter EdlingerEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9183)

Abstract

This publication presents a novel device for BCI based stroke rehabilitation, using two feedback modalities: visually, via an avatar showing the desired movements in the user’s first perspective; and via electrical stimulation of the relevant muscles. Three different kinds of movements can be trained: wrist dorsiflexion, elbow flexion and knee extension. The patient has to imagine the selected motor movements. Feedback is presented online by the device if the BCI detects the correct imagination. Results of two patients are presented showing improvements in motor control for both of them.

Keywords

Linear Discriminant Analysis Motor Imagery Stroke Survivor Functional Electrical Stimulation Control Accuracy 
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

Acknowledgements

This research has been partially supported by the European projects ComaWare (GA no. 650381), DeNeCor (ENIAC JU 2012 GA on. 324257) and CREAM (GA no. 265648).

References

  1. 1.
    World Health Organization: The top 10 causes of death. Available from: http://who.int/mediacentre/factsheets/fs310/en/
  2. 2.
    Feigin, V.L., Forouzanfar, M.H., Krishnamurthi, R., Mensah, G.A., Connor, M., Bennett, D.A., et al.: Global and regional burden of stroke during 1990–2010: findings from the global burden of disease study 2010. The Lancet 383, 245–255 (2014)CrossRefGoogle Scholar
  3. 3.
    Daly, J.J., Wolpaw, J.R.: Brain-computer interfaces in neurological rehabilitation. Lancet Neurol. 7, 1032–1043 (2008)CrossRefGoogle Scholar
  4. 4.
    Ang, K.K., Guan, C., Phua, K. S., Wang, C., Zhou, L., Tang, et al.: Brain-Computer Interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke. Front. Neuroengineering, vol. 7 (2014)Google Scholar
  5. 5.
    Zimmermann-Schlatter, A., Schuster, C., Puhan, M.A., Siekierka, E., Steurer, J.: Efficacy of motor imagery in post-stroke rehabilitation: a systematic review. J Neuroeng Rehabil. 5, 8 (2008)CrossRefGoogle Scholar
  6. 6.
    Sharma, N., Simmons, L.H., Jones, S., Day, D.J., Carpenter, A., Pomeroy, V.M., et al.: Motor imagery after subcortical stroke: a functional magnetic resonance imaging study. Stroke 40, 1315–1324 (2009)CrossRefGoogle Scholar
  7. 7.
    Liu, K.P., Lee, T.M., Chan, C.C., Hui-Chan, C.W.: Mental imagery for promoting relearning for people after stroke: a randomized controlled trial. Arch. Phys. Med. Rehabil. 85(9), 1403–1408 (2004)CrossRefGoogle Scholar
  8. 8.
    Liepert, J., Bauder, H., Miltner, W.H.R., Taub, E., Weiller, C.: Treatment induced cortical reorganization after stroke in humans. Stroke 31, 1210–1216 (2000)CrossRefGoogle Scholar
  9. 9.
    Prange, G.B., Jannink, M.J., Groothuis-Oudshoorn, C.G., Hermens, H.J., IJzerman, M.J., et al.: Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J. Rehabil. Res. Dev. 43, 171 (2006)CrossRefGoogle Scholar
  10. 10.
    Barreca, S., Wolf, S.L., Fasoli, S., Bohannon, R.: Treatment interventions for the paretic upper limb of stroke survivors: a critical review. Neurorehabilitation Neural Repair 17, 220–226 (2003)CrossRefGoogle Scholar
  11. 11.
    Ramos-Murguialday, A., Broetz, D., Rea, M., Läer, L., Yilmaz, O., Brasil, F.L., et al.: Brain-machine-interface in chronic stroke rehabilitation: a controlled study. Ann Neurol. 74, 100–108 (2013). doi: 10.1002/ana.23879 CrossRefGoogle Scholar
  12. 12.
    Glanz, M., Klawansky, S., Stason, W., Berkey, C., Chalmers, T.C.: Functional electrostimulation in poststroke rehabilitation: a meta-analysis of the randomized controlled trials. Arch. Phys. Med. Rehabil. 77, 549–553 (1996)CrossRefGoogle Scholar
  13. 13.
    Triolo, R.J., Bogie, K.: Lower extremity applications of functional neuromuscular stimulation after spinal cord injury. Top. Spinal Cord Injury Rehabil. 5, 44–65 (1999)CrossRefGoogle Scholar
  14. 14.
    Grosse-Wentrup, M., Mattia, D., Oweiss, K.: Using brain–computer interfaces to induce neural plasticity and restore function. J. Neural Eng. 8, 025004 (2011)CrossRefGoogle Scholar
  15. 15.
    Ortner, R., Ram, D., Kollreider, A., Pitsch, H., Wojtowicz, J., Edlinger, G.: Human-Computer Confluence for Rehabilitation Purposes after Stroke. In: Shumaker, R. (ed.) VAMR 2013, Part II. LNCS, vol. 8022, pp. 74–82. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Guger, C., Ramoser, H., Pfurtscheller, G.: Real-time EEG analysis with subject-specific spatial patterns for a Brain-Computer Interface (BCI). IEEE Trans. Rehab. Eng. 8, 447–456 (2000)CrossRefGoogle Scholar
  17. 17.
    Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., Müller, K.-R.: Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Process. Mag. 25(1), 41–56 (2008)CrossRefGoogle Scholar
  18. 18.
    Beebe, J.A., Lang, C.E.: Relationships and responsiveness of six upper extremity function tests during the first 6 months of recovery after stroke. J. Neurol. Phys. Ther. JNPT 33, 96 (2009)CrossRefGoogle Scholar
  19. 19.
    Taub, E., Uswatte, G., Mark, V., Morris, D.: The learned nonuse phenomenon: implications for rehabilitation. Europa medicophysica 42, 241–256 (2006)Google Scholar
  20. 20.
    Allison, B., Neuper, C.: In: Tan, D.S., Nijholt, A. (eds.) Brain-Computer Interfaces, pp. 35–54. Springer, London (2010). at http://dx.doi.org/10.1007/978-1-84996-272-8_3

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Rupert Ortner
    • 1
  • Danut-Constantin Irimia
    • 1
    • 2
  • Christoph Guger
    • 1
    • 3
  • Günter Edlinger
    • 1
    • 3
    Email author
  1. 1.Guger Technologies OGGrazAustria
  2. 2.Faculty of Electrical Engineering “Gheorghe Asachi”Technical University IasiIasiRomania
  3. 3.g.tec medical engineering GmbHSchiedlbergAustria

Personalised recommendations