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SSVEP-Based BCI for Lower Limb Rehabilitation

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Biomechatronics in Medical Rehabilitation

Abstract

SSVEPs are less vulnerable to noise than other kinds of EEG signals and have, therefore, recently become popular in BCI applications. To our knowledge, this chapter is the first to demonstrate an online asynchronous analogue SSVEP-based BCI for lower limb rehabilitation in which the movement of a robotic exoskeleton is continuously controlled by the user’s intent. Such patient participation has proved to be one of the most important factors for rehabilitating the neural system after injury or stroke. Three new and different training protocols were developed specifically for rehabilitation and tested with the ANBF. Results with six healthy participants were extremely good, with an accuracy to within a knee angle of 1° after simple training. These results are promising for the future development of brain controlled rehabilitation devices.

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Author information

Authors and Affiliations

  1. School of Electrical and Electronic Engineering, University of Leeds, Leeds, United Kingdom

    Shane Xie

  2. Department of Mechanical Engineering, The University of Auckland, Auckland, New Zealand

    Shane Xie & Wei Meng

  3. School of Information Engineering, Wuhan University of Technology, Wuhan, China

    Wei Meng

  4. The University of Auckland, Auckland, New Zealand

    Xing Song

Authors
  1. Xing Song
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  2. Shane Xie
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  3. Wei Meng
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Correspondence to Shane Xie .

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Editors and Affiliations

  1. School of Electrical and Electronic Engineering, University of Leeds, Leeds, United Kingdom

    Shane (S.Q.) Xie

  2. School of Information Engineering, Wuhan University of Technology, Wuhan, Switzerland

    Wei Meng

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Song, X., Xie, S., Meng, W. (2017). SSVEP-Based BCI for Lower Limb Rehabilitation. In: Xie, S., Meng, W. (eds) Biomechatronics in Medical Rehabilitation. Springer, Cham. https://doi.org/10.1007/978-3-319-52884-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-52884-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52883-0

  • Online ISBN: 978-3-319-52884-7

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