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1 Department of Physical Therapy, University of Illinois at Chicago, 60612; 2 Department of Physical Therapy and Human Movement Sciences, Northwestern University Medical School, Chicago, Illinois 60611; 3 Department of Systems Engineering, University of Arkansas, Little Rock, Arkansas 72204; 4 Department of Exercise and Sport Science, Oregon State University, Corvallis, Oregon 97331
Submitted 12 December 2002; accepted in final form 5 April 2003
Human upright posture is inherently unstable. To counter the mechanical effect of a large-scale perturbation such as a slip, the CNS can make adaptive adjustments in advance to improve the stability of the body center-of-mass (COM) state (i.e., its velocity and position). Such feedforward control relies on an accurate internal representation of stability limits, which must be a function of anatomical, physiological, and environmental constraints and thus should be computationally deducible based on physical laws of motion. We combined an empirical approach with mathematical modeling to verify the hypothesis that an adaptive improvement in feedforward control of COM stability correlated with a subsequent reduction in balance loss. Forty-one older adults experienced a slip during a sit-to-stand task in a block of slip trials, followed by a block of nonslip trials and a re-slip trial. Their feedforward control of COM stability was quantified as the shortest distance between its state measured at seat-off (slip onset) and the mathematically predicted feasible stability region boundary. With adaptation to repeated slips, older adults were able to exponentially reduce their incidence of falls and backward balance loss, attributable significantly to their improvement in feedforward control of stability. With exposure to slip and nonslip conditions, subjects began to select "optimal" movements that improved stability under both conditions, reducing the reliance on prior knowledge of forthcoming perturbations. These results can be fully accounted for when we assume that an internal representation of the COM stability limits guides the adaptive improvements in the feedforward control of stability.
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