• DocumentCode
    3684810
  • Title

    Assessing neuro-motor recovery in a stroke survivor with high-resolution EEG, robotics and Virtual Reality

  • Author

    Silvia Comani;Lorenzo Schinaia;Gabriella Tamburro;Lucia Velluto;Sandro Sorbi;Silvia Conforto;Biancamaria Guarnieri

  • Author_Institution
    BIND - Behavioral Imaging and Neural Dynamics Center, University “
  • fYear
    2015
  • Firstpage
    3925
  • Lastpage
    3928
  • Abstract
    One post-stroke patient underwent neuro-motor rehabilitation of one upper limb with a novel system combining a passive robotic device, Virtual Reality training applications and high resolution electroencephalography (HR-EEG). The outcome of the clinical tests and the evaluation of the kinematic parameters recorded with the robotic device concurred to highlight an improved motor recovery of the impaired limb despite the age of the patient, his compromised motor function, and the start of rehabilitation at the 3rd week post stroke. The time frequency and functional source analysis of the HR-EEG signals permitted to quantify the functional changes occurring in the brain in association with the rehabilitation motor tasks, and to highlight the recovery of the neuro-motor function.
  • Keywords
    "Electroencephalography","Training","Kinematics","Robots","Three-dimensional displays","Time-frequency analysis","Imaging"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319252
  • Filename
    7319252