Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial.

Journal: IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Published Date:

Abstract

This paper presents the preliminary findings of a multi-year clinical study evaluating the effectiveness of adding a brain-machine interface (BMI) to the MAHI-Exo II, a robotic upper limb exoskeleton, for elbow flexion/extension rehabilitation in chronic stroke survivors. The BMI was used to trigger robot motion when movement intention was detected from subjects' neural signals, thus requiring that subjects be mentally engaged during robotic therapy. The first six subjects to complete the program have shown improvements in both Fugl-Meyer Upper-Extremity scores as well as in kinematic movement quality measures that relate to movement planning, coordination, and control. These results are encouraging and suggest that increasing subject engagement during therapy through the addition of an intent-detecting BMI enhances the effectiveness of standard robotic rehabilitation.

Authors

  • Jennifer L Sullivan
  • Nikunj A Bhagat
  • Nuray Yozbatiran
    Department of Physical Medicine and Rehabilitation and The Institute for Rehabilitation and Research (TIRR) Memorial Hermann Neurorecovery Research Center, University of Texas Health Science Center at Houston, TX, USA.
  • Ruta Paranjape
  • Colin G Losey
  • Robert G Grossman
  • Jose L Contreras-Vidal
    Noninvasive Brain-Machine Interface Systems Laboratory, Department of Electrical and Computer Engineering, University of Houston, Houston, 77204-4005, USA. jlcontr2@central.uh.edu.
  • Gerard E Francisco
    TIRR Memorial Hermann and Department of PM&R, University of Texas Health Sciences Center, 1333 Moursund Street, Houston, 77030, USA. gerard.e.francisco@uth.tmc.edu.
  • Marcia K O'Malley
    Department of Mechanical Engineering, Rice University, Houston, TX, USA.