Journal of Biomechanics
Volume 40, Issue 16 , Pages 3590-3597, 2007

A balance control model of quiet upright stance based on an optimal control strategy

  • Xingda Qu

      Affiliations

    • Department of Industrial and Systems Engineering, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA
  • ,
  • Maury A. Nussbaum

      Affiliations

    • Department of Industrial and Systems Engineering, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA
    • School of Biomedical Engineering and Sciences, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA
    • Corresponding Author InformationCorresponding author. Department of Industrial and Systems Engineering, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA. Tel.: +15402316053; fax: +15402313322.
  • ,
  • Michael L. Madigan

      Affiliations

    • School of Biomedical Engineering and Sciences, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA
    • Department of Engineering Science and Mechanics, Virginia Tech, 250 Durham Hall (0118), Blacksburg, VA 24061, USA

Accepted 7 June 2007. published online 15 July 2007.

Abstract 

Models of balance control can aid in understanding the mechanisms by which humans maintain balance. A balance control model of quiet upright stance based on an optimal control strategy is presented here. In this model, the human body was represented by a simple single-segment inverted pendulum during upright stance, and the neural controller was assumed to be an optimal controller that generates ankle control torques according to a certain performance criterion. This performance criterion was defined by several physical quantities relevant to sway. In order to accurately simulate existing experimental data, an optimization procedure was used to specify the set of model parameters to minimize the scalar error between experimental and simulated sway measures. Thirty-two independent simulations were performed for both younger and older adults. The model's capabilities, in terms of reflecting sway behaviors and identifying aging effects, were then analyzed based on the simulation results. The model was able to accurately predict center-of-pressure-based sway measures, and identify potential changes in balance control mechanisms caused by aging. Correlations between sway measures and model parameters are also discussed.

Keywords: Balance control, Optimal control strategy, Aging, Sway, Simulation

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PII: S0021-9290(07)00265-5

doi:10.1016/j.jbiomech.2007.06.003

Journal of Biomechanics
Volume 40, Issue 16 , Pages 3590-3597, 2007