Journal of Neurophysiology, Vol 73, Issue 3 1201-1222, Copyright © 1995 by APS

ARTICLES

Measurements of human force control during a constrained arm motion using a force-actuated joystick

J. McIntyre, E. V. Gurfinkel, M. I. Lipshits, J. Droulez and V. S. Gurfinkel
Laboratoire de Physiologie de la Perception et de l'Action, College de France, Paris.

1. When interacting with the environment, human arm movements may be prevented in certain directions (i.e., when sliding the hand along a surface) resulting in what is called a "constrained motion." In the directions that the movement is restricted, the subject is instead free to control the forces against the constraint. 2. Control strategies for constrained motion may be characterized by two extreme models. Under the active compliance model, an essentially feedback-based approach, measurements of contact force may be used in real time to modify the motor command and precisely control the forces generated against the constraint. Under the passive compliance model the motion would be executed in a feedforward manner, using an internal model of the constraint geometry. The feedforward model relies on the compliant behavior of the passive mechanical system to maintain contact while avoiding excessive contact forces. 3. Subjects performed a task in which they were required to slide the hand along a rigid surface. This task was performed in a virtual force environment in which contact forces were simulated by a two-dimensional force-actuated joystick. Unknown to the subject, the orientation of the surface constraint was varied from trial to trial, and contact force changes induced by these perturbations were measured. 4. Subjects showed variations in contact force correlated with the direction of the orientation perturbation. "Upward" tilts resulted in higher contact forces, whereas "downward" tilts resulted in lower contact forces. This result is consistent with a feedforward-based control of a passively compliant system. 5. Subject responses did not, however, correspond exactly to the predictions of a static analysis of a passive, feedforward-controlled system. A dynamic analysis reveals a much closer resemblance between a passive, feedforward model and the observed data. Numerical simulations demonstrate that a passive, dynamic system model of the movement captures many more of the salient features observed in the measured human data. 6. We conclude that human subjects execute surface-following motions in a largely feedforward manner, using an a priori model of the surface geometry. The evidence does not suggest that active, real time use of force feedback is used to guide the movement or to control limb impedance. We do not exclude, however, the possibility that the internal model of the constraint is updated at somewhat longer latencies on the basis of proprioceptive information.

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