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A spelling device for the paralysed

Author

Listed:
  • N. Birbaumer

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen
    University of Padova)

  • N. Ghanayim

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen)

  • T. Hinterberger

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen)

  • I. Iversen

    (University of North Florida)

  • B. Kotchoubey

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen)

  • A. Kübler

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen)

  • J. Perelmouter

    (Institute of Medical Psychology and Behavioural Neurobiology, University of Tbingen)

  • E. Taub

    (University of Alabama)

  • H. Flor

    (Humboldt-University)

Abstract

When Jean-Dominique Bauby suffered from a cortico-subcortical stroke that led to complete paralysis with totally intact sensory and cognitive functions, he described his experience in The Diving-Bell and the Butterfly1 as “something like a giant invisible diving-bell holds my whole body prisoner”. This horrifying condition also occurs as a consequence of a progressive neurological disease, amyotrophic lateral sclerosis, which involves progressive degeneration of all the motor neurons of the somatic motor system. These ‘locked-in’ patients ultimately become unable to express themselves and to communicate even their most basic wishes or desires, as they can no longer control their muscles to activate communication devices. We have developed a new means of communication for the completely paralysed that uses slow cortical potentials (SCPs) of the electro-encephalogram to drive an electronic spelling device.

Suggested Citation

  • N. Birbaumer & N. Ghanayim & T. Hinterberger & I. Iversen & B. Kotchoubey & A. Kübler & J. Perelmouter & E. Taub & H. Flor, 1999. "A spelling device for the paralysed," Nature, Nature, vol. 398(6725), pages 297-298, March.
    • Handle: RePEc:nat:nature:v:398:y:1999:i:6725:d:10.1038_18581
    DOI: 10.1038/18581
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    Citations

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    Cited by:

    1. Pavlov, A.N. & Grishina, D.S. & Runnova, A.E. & Maksimenko, V.A. & Pavlova, O.N. & Shchukovsky, N.V. & Hramov, A.E. & Kurths, J., 2019. "Recognition of electroencephalographic patterns related to human movements or mental intentions with multiresolution analysis," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 230-235.
    2. Iñaki Iturrate & Jonathan Grizou & Jason Omedes & Pierre-Yves Oudeyer & Manuel Lopes & Luis Montesano, 2015. "Exploiting Task Constraints for Self-Calibrated Brain-Machine Interface Control Using Error-Related Potentials," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    3. Peter Loos & René Riedl & Gernot Müller-Putz & Jan Brocke & Fred Davis & Rajiv Banker & Pierre-Majorique Léger, 2010. "NeuroIS: Neuroscientific Approaches in the Investigation and Development of Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(6), pages 395-401, December.
    4. Andrey Eliseyev & Tetiana Aksenova, 2016. "Penalized Multi-Way Partial Least Squares for Smooth Trajectory Decoding from Electrocorticographic (ECoG) Recording," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-19, May.
    5. Laura Acqualagna & Loic Botrel & Carmen Vidaurre & Andrea Kübler & Benjamin Blankertz, 2016. "Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-19, February.
    6. Yasuhiko Nakanishi & Takufumi Yanagisawa & Duk Shin & Ryohei Fukuma & Chao Chen & Hiroyuki Kambara & Natsue Yoshimura & Masayuki Hirata & Toshiki Yoshimine & Yasuharu Koike, 2013. "Prediction of Three-Dimensional Arm Trajectories Based on ECoG Signals Recorded from Human Sensorimotor Cortex," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-9, August.
    7. Martin Spüler, 2019. "Questioning the evidence for BCI-based communication in the complete locked-in state," PLOS Biology, Public Library of Science, vol. 17(4), pages 1-5, April.
    8. Ujwal Chaudhary & Bin Xia & Stefano Silvoni & Leonardo G Cohen & Niels Birbaumer, 2017. "Brain–Computer Interface–Based Communication in the Completely Locked-In State," PLOS Biology, Public Library of Science, vol. 15(1), pages 1-25, January.
    9. Pieter-Jan Kindermans & Martijn Schreuder & Benjamin Schrauwen & Klaus-Robert Müller & Michael Tangermann, 2014. "True Zero-Training Brain-Computer Interfacing – An Online Study," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-13, July.
    10. Johannes Höhne & Elisa Holz & Pit Staiger-Sälzer & Klaus-Robert Müller & Andrea Kübler & Michael Tangermann, 2014. "Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
    11. Heung-Il Suk & Siamac Fazli & Jan Mehnert & Klaus-Robert Müller & Seong-Whan Lee, 2014. "Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-15, February.
    12. Florin Popescu & Siamac Fazli & Yakob Badower & Benjamin Blankertz & Klaus-R Müller, 2007. "Single Trial Classification of Motor Imagination Using 6 Dry EEG Electrodes," PLOS ONE, Public Library of Science, vol. 2(7), pages 1-5, July.

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