Development and experimental validation of a mathematical model for friction between fabrics and a volar forearm phantom.

An analytical mathematical model for friction between a fabric strip and the volar forearm has been developed and validated experimentally. The model generalizes the common assumption of a cylindrical arm to any convex prism, and makes predictions for pressure and tension based on Amontons' law. This includes a relationship between the coefficient of static friction (mu) and forces on either end of a fabric strip in contact with part of the surface of the arm and perpendicular to its axis. Coefficients of friction were determined from experiments between arm phantoms of circular and elliptical cross-section (made from Plaster of Paris covered in Neoprene) and a nonwoven fabric. As predicted by the model, all values of mu calculated from experimental results agreed within +/- 8 per cent, and showed very little systematic variation with the deadweight, geometry, or arc of contact used. With an appropriate choice of coordinates the relationship predicted by this model for forces on either end of a fabric strip reduces to the prediction from the common model for circular arms. This helps to explain the surprisingly accurate values of mu obtained by applying the cylindrical model to experimental data on real arms.

Learning optimal adaptation strategies in unpredictable motor tasks.

Picking up an empty milk carton that we believe to be full is a familiar example of adaptive control, because the adaptation process of estimating the carton's weight must proceed simultaneously with the control process of moving the carton to a desired location. Here we show that the motor system initially generates highly variable behavior in such unpredictable tasks but eventually converges to stereotyped patterns of adaptive responses predicted by a simple optimality principle. These results suggest that adaptation can become specifically tuned to identify task-specific parameters in an optimal manner.