• DocumentCode
    3685593
  • Title

    A multi-channel biomimetic neuroprosthesis to support treadmill gait training in stroke patients

  • Author

    Noelia Chia;Emilia Ambrosini;Walter Baccinelli;Antonio Nardone;Marco Monticone;Giancarlo Ferrigno;Alessandra Pedrocchi;Simona Ferrante

  • Author_Institution
    Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo Da Vinci, 32, 20133, Italy
  • fYear
    2015
  • Firstpage
    7159
  • Lastpage
    7162
  • Abstract
    This study presents an innovative multi-channel neuroprosthesis that induces a biomimetic activation of the main lower-limb muscles during treadmill gait training to be used in the rehabilitation of stroke patients. The electrostimulation strategy replicates the physiological muscle synergies used by healthy subjects to walk on a treadmill at their self-selected speed. This strategy is mapped to the current gait sub-phases, which are identified in real time by a custom algorithm. This algorithm divides the gait cycle into six sub-phases, based on two inertial sensors placed laterally on the shanks. Therefore, the pre-defined stimulation profiles are expanded or stretched based on the actual gait pattern of each single subject. A preliminary experimental protocol, involving 10 healthy volunteers, was carried out to extract the muscle synergies and validate the gait-detection algorithm, which were afterwards used in the development of the neuroprosthesis. The feasibility of the neuroprosthesis was tested on one healthy subject who simulated different gait patterns, and a chronic stroke patient. The results showed the correct functioning of the system. A pilot study of the neurorehabilitation treatment for stroke patients is currently being carried out.
  • Keywords
    "Muscles","Electromyography","Training","Physiology","Sensors","Biomechanics","Integrated circuits"
  • 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.2015.7320043
  • Filename
    7320043