• DocumentCode
    1568197
  • Title

    Neural muscular delays in Equilibrium Point model of human arm trajectory

  • Author

    Chen, Kai ; Swift, M.S.K. ; Foulds, Richard

  • Author_Institution
    Dept. of Biomed. Eng., New Jersey Inst. of Technol., Newark, NJ
  • fYear
    2009
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    The aim of this paper is to investigate the human arm´s sensory-motor control mechanism in the trajectory planning of arm movement in the transverse plane. According to the equilibrium point hypothesis, the equilibrium configuration of joint angles and muscle torques are defined as a single variable called the equilibrium point (EP). Further, control systems reset the EP by shifting the invariant characteristic (IC) which initiates muscle activation and movement. The duration and sequences of shifting, however, are unclear. This work utilizes the spike triggering averaging (STA) technique integrated with simultaneous EMG and joint positions to find the sequences, but the nature of EMG signal does not favor the STA. The raw EMG signals were used to project sequences and time delay for the model of simulation. Our results exhibit an improvement in trajectory accuracy with decreased time delay.
  • Keywords
    biocontrol; biomechanics; electromyography; medical signal processing; neurophysiology; physiological models; EMG signal; equilibrium point hypothesis model; human arm movement; human arm sensory-motor control mechanism; invariant characteristics; muscle activation; muscle torque; neural muscular delays; spike triggering averaging technique; Control systems; Damping; Delay effects; Elbow; Electrodes; Electromyography; Humans; Muscles; Signal to noise ratio; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioengineering Conference, 2009 IEEE 35th Annual Northeast
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-4362-8
  • Electronic_ISBN
    978-1-4244-4364-2
  • Type

    conf

  • DOI
    10.1109/NEBC.2009.4967749
  • Filename
    4967749