An optimal control model of human balance: can it provide theoretical insight to neural control of movement?

A physiologically plausible model for control of human postural balance, combining optimal state estimation and control, is proposed. The linear dynamics of three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These sensors are mated with a two degree of freedom model of planar body dynamics. Linear quadratic optimal control theory is used to design the state feedback and estimation gains. Free parameters for the overall system set the form of the control objective and the sensory precision of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with human responses to alterations in sensory conditions. For a single set of parameters, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Sensitivity studies demonstrate that the model is robust to parameter variations, consistent with observed behavior. A physiological structure is proposed for learning and implementing the necessary computations. The model may be useful as a diagnostic tool for detecting contributing factors to poor balance.