• DocumentCode
    1396390
  • Title

    A Method for the Control of Multigrasp Myoelectric Prosthetic Hands

  • Author

    Dalley, Skyler Ashton ; Varol, Huseyin Atakan ; Goldfarb, Michael

  • Author_Institution
    Dept. of Mech. Eng., Vanderbilt Univ., Nashville, TN, USA
  • Volume
    20
  • Issue
    1
  • fYear
    2012
  • Firstpage
    58
  • Lastpage
    67
  • Abstract
    This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation.
  • Keywords
    biomedical electrodes; data gloves; electromyography; medical control systems; medical signal processing; prosthetics; random sequences; EMG signals; data glove; multigrasp myoelectric prosthetic hand motion controller; random sequences; surface electromyography electrodes; virtual prosthesis; Actuators; Data gloves; Electrodes; Electromyography; Grasping; Prosthetics; Thumb; Biomechatronics; electromyography (EMG); multigrasp prosthesis; myoelectric control; transradial prosthesis; Biomechanics; Calibration; Computer Systems; Data Collection; Electrodes; Electromyography; Electronics; Fingers; Hand; Hand Strength; Humans; Motion; Muscle Contraction; Prostheses and Implants; Prosthesis Design; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2011.2175488
  • Filename
    6101579