• DocumentCode
    2385855
  • Title

    Reconstruction and EMG-informed control, simulation and analysis of human movement for athletics: Performance improvement and injury prevention

  • Author

    Demircan, Emel ; Khatib, Oussama ; Wheeler, Jason ; Delp, Scott

  • Author_Institution
    Mech. Eng. Dept., Stanford Univ., Stanford, CA, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    6534
  • Lastpage
    6537
  • Abstract
    In this paper we present methods to track and characterize human dynamic skills using motion capture and electromyographic sensing. These methods are based on task-space control to obtain the joint kinematics and extract the key physiological parameters and on computed muscle control to solve the muscle force distribution problem. We also present a dynamic control and analysis framework that integrates these metrics for the purpose of reconstructing and analyzing sports motions in real-time.
  • Keywords
    electromyography; gait analysis; medical signal processing; motion control; signal reconstruction; EMG; athletics; electromyography; human movement; motion capture; muscle force distribution; reconstruction; task-space control; Algorithms; Athletic Injuries; Biofeedback, Psychology; Electromyography; Humans; Movement; Physical Fitness; Sports; Task Performance and Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5333148
  • Filename
    5333148