EEG-based BCI for the linear control of an upper-limb neuroprosthesis

Carmen Vidaurre, Christian Klauer, Thomas Schauer, Ander Ramos-Murguialday, Klaus Robert Müller

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


Assistive technologies help patients to reacquire interacting capabilities with the environment and improve their quality of life. In this manuscript we present a feasibility study in which healthy users were able to use a non-invasive Motor Imagery (MI)-based brain computer interface (BCI) to achieve linear control of an upper-limb functional electrical stimulation (FES) controlled neuro-prosthesis. The linear control allowed the real-time computation of a continuous control signal that was used by the FES system to physically set the stimulation parameters to control the upper-limb position. Even if the nature of the task makes the operation very challenging, the participants achieved a mean selection accuracy of 82.5% in a target selection experiment. An analysis of limb kinematics as well as the positioning precision was performed, showing the viability of using a BCI–FES system to control upper-limb reaching movements. The results of this study constitute an accurate use of an online non-invasive BCI to operate a FES-neuroprosthesis setting a step toward the recovery of the control of an impaired limb with the sole use of brain activity.

Original languageEnglish
Pages (from-to)1195-1204
Number of pages10
JournalMedical Engineering and Physics
Issue number11
Publication statusPublished - 2016 Nov 1


  • Brain–computer interfacing
  • Functional electrical stimulation
  • Motor imagery
  • Neuralprosthesis

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering


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