Chapter 2. Prehension

Subject Index
(Letters after page numbers: f=figure; n=foomote; t=table)
A
Abduction (movement), 358
Acceleration of movement
effect of visual information on, 179
during grasping. 145,146,148
and object velocity. 148
peak, of transport component, 145
in perturbation studies, 159, 161
during pointing, 146
profie. and central vision, 18 1-83, 182f
time, 126f
Accessibility consvaints
and grasp component, 151-52
and transport component, 151-52
Accuracy, of performance, and visual
Acetylcholine, and sweating, 218
Action theory, of planning of prehension, 64
Activation function, of a neural network,
Active manipulation, 336-37
Active touch, 229,267f. 268.2%. 298,336
Actual Grasp Schema, 195f. 196,291f
Adaptation, by a neural network, 389-95
Adduction (movement), 358
Adduction grasp, 19t, 28f. 29.35.36.3726
Adhesion, of skin, 212f. 212-13
Amonton's laws of friction (equation), 211,
309. Coefficient of
friction; Cone of friction; Friction
Analytic measures, of grasps, 264-66.332
Anamcal constraints, on grasping, 325
Anatomy, upper limb
innervation, 359-67,365f, 366-67t
joints, movement, and degrees of freedom,
muscles, 359.3604%
planes of the body, 349-50
skeletal smcture, 351
Aperture
effect of visual information on. 178-86
grasp
information, 199-200
385-86.386f
375-76.380
35 1-59
and opposition vector, 145-46
and perturbations of object
dimtion, 16Of
maximum. Aperture, peak
peak
and Coordinated Control Program,
190-91
and lack of sensory information, 189
and movement time, 150
and object size, 152, 169,170f. 172f
and pad opposition, 169
and palm opposition, 169
and peripheral vision, 181f
in perturbation studies, 145,167
and precision requirements, 169
463
in perturbation studies, 158f. 159, 167
profiles, 49-51.50f. 52f
Ap&rine glands, 214
Approach vector
and opposition vector, 106f. 107,151,
288f
and virtual fingers. 151
Approach Vector Selector model, 98-101, 99f.
loof. 188
Arm. see alsQ Forearm; Transport component;
Upper limb
ballistic contmller of, 129
ballistic movement of, 148
degrees of freedom, 113-14,354t
and hand, sensorimotor integration of
perturbation studies, 156-66
in reaching and grasping, 141-46
task requirements and object
propexties, 146-56
innervation, 368t
joints, 361t
movements, control of, 118-44
muscles, 361t
in perturbation studies, l58f. 159
and sensory information. 199
skeletal structure, 352f
trajectories, 129f
ARMAX computational model, 148
Artificial hand. % Prosthetic hand
Artificial neural networks. sec; Neural
networks
Assemblage models of prehension, 383
Asymmetric velocity profiles, 123,125,127,
128,130f. Fins' Law;
Recision requirements
Autonomic motor system, and eccrine sweat
glands, 214-222,221f, 2972
B
Backward chaining, of expert systems, 84
Bag, hooking over fingers, 36
Ball, as grasped object, 21,3 1
Ball grasp, 19t, 37Ot
Ballistic
controllers, 11 1
movement. 53.11 1,148
Ballpark model of prehension, 56f, 56-57,
187-89, 188f, 200-201,294
Basketball, as grasped object, 237
Baton, twirling, 276-78,277f
Bearing, ball, as grasped object, 21
Behavioral studies, in relation to
prehension, 9
Binocular vision. and distance information,
184
Biomechanical
constrajnts, on grasping, 325