• DocumentCode
    3379949
  • Title

    Prediction gait during ascending stair by using artificial neural networks

  • Author

    Prasertsakul, Thunyanoot ; Poonsiri, Jutamanee ; Charoensuk, Warakorn

  • Author_Institution
    Dept. of Biomed. Eng., Mahidol Univ., Nakornprathom, Thailand
  • fYear
    2012
  • fDate
    5-7 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Walking up or down stairs is an important activity for human lives. Gait pattern of this activity is as same as walking except the range of motion and phase of muscles activities. Many studies have been focused on behavior of this motion. Two cameras and electromyogram (EMG) are the applications used in this study and analysis the motion. To determine the relationship of the both data, it can be performed in many techniques but in this study used artificial neural network model. Nonlinear Autoregressive model with exogenous (NARX) input was applied to this study to define the relationship between the electromyogram of eight muscles and angular displacement of knee and ankle joints of both legs. The results show that the predicted data from NARX were similar to the measured data.
  • Keywords
    autoregressive processes; bone; cameras; electromyography; gait analysis; medical signal processing; muscle; neural nets; EMG; NARX model; angular displacement; ankle joints; artificial neural networks; cameras; electromyogram; gait pattern; human lives; knee; legs; muscle activities; muscle motion; nonlinear autoregressive-with-exogenous input model; walking; Artificial neural networks; Electromyography; Joints; Knee; Legged locomotion; Muscles; EMG; gait; neural network; nonlinear autoregressive; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering International Conference (BMEiCON), 2012
  • Conference_Location
    Ubon Ratchathani
  • Print_ISBN
    978-1-4673-4890-4
  • Type

    conf

  • DOI
    10.1109/BMEiCon.2012.6465464
  • Filename
    6465464