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Brain-computer interface controlled robotic gait orthosis.

An H Do1, Po T Wang, Christine E King

  • 1Department of Neurology, University of California, Irvine, CA, USA. and@uci.edu.

Journal of Neuroengineering and Rehabilitation
|December 11, 2013
PubMed
Summary
This summary is machine-generated.

Brain-computer interface (BCI) controlled robotic gait orthoses show promise for restoring walking in individuals with spinal cord injury (SCI). This novel approach may reduce health complications and improve independence for those with paraplegia or tetraplegia.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Medicine

Background:

  • Spinal cord injury (SCI) frequently leads to wheelchair dependence, causing significant medical comorbidities and high healthcare costs.
  • Restoring ambulation could mitigate these health issues, enhance independence, and improve quality of life for individuals with SCI.
  • Current biomedical solutions cannot reverse neurological deficits, necessitating novel approaches like brain-computer interfaces.

Purpose of the Study:

  • To investigate the feasibility of using a brain-computer interface (BCI) to control a robotic gait orthosis (RoGO) for restoring ambulation in individuals with SCI.
  • To develop and test an electroencephalogram (EEG) prediction model for real-time BCI control of lower extremity prostheses.

Main Methods:

  • EEG data were recorded from one able-bodied and one SCI subject during kinesthetic motor imagery (KMI) of walking.
  • An EEG prediction model was generated for online BCI operation, controlling a commercial RoGO system over a treadmill.
  • Subjects performed five 5-minute online sessions, ambulating via the BCI-RoGO system, with performance assessed via cross-correlation and error rates.

Main Results:

  • The EEG prediction model achieved an offline accuracy of 86.30% across subjects.
  • A strong positive correlation (0.812) was observed between instructional cues and BCI-RoGO walking epochs (p<10(-4)).
  • The system demonstrated high reliability with an average of 0.8 false alarms per session and no omissions.

Conclusions:

  • Preliminary results suggest that restoring brain-controlled ambulation after SCI is feasible.
  • Future research will focus on testing this BCI-RoGO system in a larger SCI population.
  • Successful implementation could lead to the development of BCI-controlled prostheses for overground walking and potentially improve outcomes in incomplete SCI.