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

Med Eng Phys. 2016 Nov;38(11):1195-1204. doi: 10.1016/j.medengphy.2016.06.010. Epub 2016 Jul 12.


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.

Keywords: Brain–computer interfacing; Functional electrical stimulation; Motor imagery; Neuralprosthesis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain-Computer Interfaces*
  • Calibration
  • Electric Stimulation
  • Electroencephalography*
  • Feedback, Physiological
  • Humans
  • Linear Models
  • Neural Prostheses*
  • Upper Extremity*