• DocumentCode
    122624
  • Title

    Human postural stability model and artificial neural network for prediction the center of pressure

  • Author

    Prasertsakul, Thunyanoot ; Wongsawat, Y. ; Charoensuk, Warakorn

  • Author_Institution
    Dept. of Biomed. Eng., Mahidol Univ., Nakorn Pathom, Thailand
  • fYear
    2014
  • fDate
    19-21 March 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Human postural stability is the necessary function for human livings. This function controls the whole body into the upright position. To understand the behavior of human balance control can be achieved by many methods. The mathematical model is a general technique for explanation the mechanism of biomechanics. The human postural stability system has been designed into the mathematical model. The model at sagittal and coronal plane utilized to describe the motion. This study focused on the model at coronal plane. There were two methods which performed. The first method was to use the mathematical formula for determination the COP. Second, there was the human postural stability model and artificial neural network to predict the COP. The result indicated that both methods could determine the COP, but the neural network has less error than the other method. However, there was some limitation to define the suitable parameter of neural network for getting better output.
  • Keywords
    biology computing; biomechanics; neural nets; COP prediction; artificial neural network; biomechanics; coronal plane; human balance control behavior; human postural stability model; mathematical model; pressure center prediction; sagittal plane; Biological system modeling; Biomechanics; Mathematical model; Predictive models; Stability analysis; Torque; Human postural stability; NARX; center of pressure; mathematical model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering Congress (iEECON), 2014 International
  • Conference_Location
    Chonburi
  • Type

    conf

  • DOI
    10.1109/iEECON.2014.6925900
  • Filename
    6925900