• DocumentCode
    2840
  • Title

    Evaluation of a Noninvasive Command Scheme for Upper-Limb Prostheses in a Virtual Reality Reach and Grasp Task

  • Author

    Kaliki, R.R. ; Davoodi, R. ; Loeb, Gerald E.

  • Author_Institution
    Infinite Biomed. Technol., Baltimore, MD, USA
  • Volume
    60
  • Issue
    3
  • fYear
    2013
  • fDate
    Mar-13
  • Firstpage
    792
  • Lastpage
    802
  • Abstract
    C5/C6 tetraplegic patients and transhumeral amputees may be able to use voluntary shoulder motion as command signals for a functional electrical stimulation system or transhumeral prosthesis. Stereotyped relationships, termed “postural synergies,” among the shoulder, forearm, and wrist joints emerge during goal-oriented reaching and transport movements as performed by able-bodied subjects. Thus, the posture of the shoulder can potentially be used to infer the desired posture of the elbow and forearm joints during reaching and transporting movements. We investigated how well able-bodied subjects could learn to use a noninvasive command scheme based on inferences from these postural synergies to control a simulated transhumeral prosthesis in a virtual reality task. We compared the performance of subjects using the inferential command scheme (ICS) with subjects operating the simulated prosthesis in virtual reality according to complete motion tracking of their actual arm and hand movements. Initially, subjects performed poorly with the ICS but improved rapidly with modest amounts of practice, eventually achieving performance only slightly less than subjects using complete motion tracking. Thus, inferring the desired movement of distal joints from voluntary shoulder movements appears to be an intuitive and noninvasive approach for obtaining command signals for prostheses to restore reaching and grasping functions.
  • Keywords
    bioelectric phenomena; biomechanics; inference mechanisms; medical control systems; motion measurement; prosthetics; virtual reality; C5 tetraplegic patients; C6 tetraplegic patients; able bodied subjects; command signals; complete motion tracking; distal joints; elbow joint posture; forearm joint posture; functional electrical stimulation system; goal oriented reaching; grasping functions; hand movements; inferential command scheme; noninvasive command scheme; postural synergies; reaching functions; reaching movements; shoulder posture; simulated prosthesis; stereotyped relationships; transhumeral amputees; transhumeral prosthesis; transport movements; upper limb prostheses; virtual reality task; voluntary shoulder motion; wrist joints; Artificial neural networks; Elbow; Joints; Shoulder; Training; Virtual reality; Wrist; Amputee; C5/C6; grasping; neural networks; quadriplegic; reaching; synergies; transhumeral; upper-limb prostheses; virtual reality (VR); Artificial Limbs; Electromyography; Hand Strength; Humans; Neural Networks (Computer); Range of Motion, Articular; Shoulder; Signal Processing, Computer-Assisted; Task Performance and Analysis; Upper Extremity; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2012.2185494
  • Filename
    6138294