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SSVEP-Based BCI for Lower Limb Rehabilitation

  • Xing Song
  • Shane Xie
  • Wei Meng
Chapter

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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Electrical and Electronic EngineeringUniversity of LeedsLeedsUnited Kingdom
  2. 2.Department of Mechanical EngineeringThe University of AucklandAucklandNew Zealand
  3. 3.School of Information EngineeringWuhan University of TechnologyWuhanChina
  4. 4.The University of AucklandAucklandNew Zealand

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