Chapter 2. Prehension

Chapter 5 - Movement Before Contact 127
target contact increased with target size. Worringham (1987) showed
that impact forces also increase linearly with target size.
The above findings suggest that the target surface was used to decelerate
the limb. MacKenzie (1992) examined the effects of target
surface and pointing implement on 3D kinematics in a Fitts’ aiming
task. Conditions for Index of Difficulty (ID) included: 2 amplitudes
(30,40 cm) and 4 target diameters (1,2,4, 8 cm). These were factorially
combined with 2 implements (index finger tip or pen tip) and 2
target types (hole or solid target). Eight adults made discrete midline
aiming movements to vertically placed targets. On each trial, subjects
placed the pointer in a constant start position. After a ‘ready’ prompt
for preparation, on a ‘go’ signal subjects moved as quickly and accurately
as possible to the target. The OPTOTRAK system (Northern
Digital, Waterloo) collected 3D coordinates of position of the implement
tip at 200 Hz. MT results replicated Fitts’ Law. Kinematic differences
among the pointing implement and target surface conditions
showed: the pen was faster (5 18 ms), with greater, earlier peak kinematic
values than the finger tip (550 ms); subjects had lower peak
kinematic values and a greater proportion of time decelerating to the
hole target (70%, 408 ms) than the solid target (a%, 310 ms). Thus
it appears that, in addition to the precision effects of target size, the
target surface was used to decelerate the aiming movement, since subjects
spent a longer proportion of time in the deceleration phase when
aiming to the hole. This demonstrates that humans can take advantage
of contact forces in interaction with objects, and the importance of
subject initiated deceleration control when decelerative forces due to
impact are not available (see also Milner & Ijaz, 1990; Teasdale &
Schmidt, 1991).
Bullock and Grossberg (1986, 1988, 1989) developed a model
that produced both symmetric and asymmetric velocity profiles. The
Vector Integration to Endpoint model, VITE, (see Figure 5.6)
produces arm trajectories from a target position (Step 1’). A target
position command, T, contains desired muscle lengths for all
trajectory-controlling muscles. An internal model of the muscle’s
present length, P, is maintained. The arm trajectory basically tracks
the evolving state of the P. A difference vector, V, is computed
between the desired and current muscle lengths. A time-varying GO
signal, G, gates V to the internal model, which in turn integrates V
through time. The size of the GO signal determines the speed at which
the limb will move. The difference vector is updated as follows: