speed, and grasping, 151 terms abduction, 358 adduction, 358 circumduction, 358 depression, 357f, 358 elevation, 357f, 358 extension, 358 flexion, 358 opposition, 358 pronation, 357f, 358 protraction, 358 radial deviation, 357f. 358 retraction, 358 rotation, 358 supination, 357f, 358 ulnar deviation, 357f, 358 unrestrained, 191 variability, 69 Movement time and Fins' Law, 146 and maximum aperture, 150 and object velocity, 149f Moveslow Schema and ballpark model, 188f and palm-focused model of grasping, 194, 196 Mug, as-g& d object, 21,31,33f, 35.80, 8<strong>2.</strong>86. g7 Muscles . activation commands, 135-38 computation of, 136f, 137f, 138f by extrinsic object ropemes. 53 degrees of freedom, f14 during enclosing, 192,193f, 194 equilibrium configuration, 122 forearm EMG activity in finger opening and pinching, 193f level commands, and neural networks, 135-38 ~~~ _. linearization model (MLN), 128x1 pectoral girdle, 359 during preshaping, 192-94, 193f receptors, 226,228 and stable gras 204 of upper limb, fb-64t Myoelectric prosthetic hand, 404-5 Subject Index 473 topologies, 384-89 addtive, 389-95.399 a icial, 383,384-95 characteristics, 85.384 for choosing virtual finger mappings, 91-93,92f connectivity pattern, 386f, 387f for grasp selection, 85f, 85-90, 88f and heteroassociative memory, 95.97, 395-99,396f, 398f and joint trajectories, 131-34, 132f, 134f, 200 layers, 387-88 and mapping virtual fingers, 289 and muscle level commands, 135-38, 136f, 137f. 138f. 200 and parallel distributed processing, 383, 387-88 pattern association and com letion, 395 planning for hand location, 84-101 planning for palm orientation, 101 -5 processing, 395,400 training, 86.91-93.97, 131-3<strong>2.</strong>388-94, 399-400 types. 382-83 Neural task plans, 70-76.71f. 73f, 74f Neurally interfaced control system, for paralyzed humans, 256 Neurmal models of rehension, 382 Nippers grasp, 2% 3%t, 372f. 375 Object prFmes and coe icient of friction, 281 as constraints on grasping, 308t, 310-11, 325 detection of, 142-43 effect on velocity of grasping, 49-53, 5Of, 52f extrinsic, 53,76,79-80, 143, 199, 330-3 1 and force application, 200 and grasping, 199,330-31 hardness, 231,232,233t intrinsic, 51,53,76-79, 143.196-97, 199,330,331 and kinemahc landmarks, 155 length, 229 orientation, 53,7940,162 N perception of, 76-80,105,231-34 Natural grasp, ma ping between object size and planning opposition space, 76-80.287 and grasp, 17% and prehensile classificatlons, 2<strong>2.</strong>25 Needle, as grasped object, 21 and sensory information, 233 Nerves, of upper limb, 366-67t and setting up cpposition space, 146-56, Network models of prehension, 382 293 Neural constraints, on grasping, 308t, 325 shape, 152-53.162-63, 165,231,232, Neural events, and phases of prehension, 61 233t. 234,261-6<strong>2.</strong>263.374-75 Neural networks. see ~ S Computational Q and stable gmp, 204,281 models of prehension stxucmral, 231,233t activation functions and network surface. . 231.233t. . . 261-62 (Letters after page numbers: f=figure; n=fmtnote; t-table.) 0
474 THE GRASPING HAND and task requirements, 80-83, 146-56 temperature, 23 1,233t texture, 156.23 1,232,233t. 234,249, 253 and transport component, 199 volume, 231,233t weight, 76, 154-56,229,230,231,233t Objects. Direction, of object; Distance, of object; Object properties; Objects, grasping and handling; Size, of object; Surface, of object; Texture, of object; Velocity, of object; Weight, of object Objects, grasping and handling active objects, 271,273 bag, hooking over fingers, 36 ball, 21.31 ball bearing, 21 basketball, 237 baton, twirling, 276-78,277f bottle, removing plug from, 52f box, 21 chalk, 27 chopsticks, 36,375 cigarette, 25,29,31,271 cord, tying knot in, 35,271 cylinder, 5Of, 51,89f dowels, 155-56.163-65. 164f, 166-69, 168f, 172f. 189,254f, 261-62, 286f drill, 27 glass, 275% 276 golf ball, 237 hammer, 31,61,67,68f, 69,203,283 lid, screwing, 28 mug, 21,31,33f, 35,80,82, 86, 187 needle, 21 page, of book, 21 paper. sheet of, 21 passive objects, 271.273 peg, pick up and insert in hole, 65-67, 66f pen, 21,27,28 pencil, 275 releasing, 278-79 rods, 229 rubber bulb or syringe, 27 sandpaper, 247,249,250f scissors. 375 screwdriver, 4-6,31, 151-52 silk, 247,249,250f sphere, 89f suede, 247,249,250f suitcase, 21.29.35 teacup, 3 1 top, turning, 25 watch, winding, 28 Opposition. see a l s Grasp ~ types; Opposition space; Pad opposition; Palm opposition; Side opposition definition, 31,358 dynamic combinations, 35-36,271,377, 378-79t, 380 and lifting, 235f as movement, 358 pad, definition, 31,32f, 33,34f palm, definition, 31,32f, 33,34f prehensile postures, 32f as prehensile primitive, 31,32f, 33 selecting opposable surfaces, 83-90 using object and task requirements, 83-90 side. definition, 3 1,32f, 33,34f state variables of, 39 thumb, 3 In and virtual fingers, 34f, 377,378-79t, 380 oppOsi$on space classlfications, 30-36.373 defition, 38-39,142n and degrees of freedom, 41 and grasp strategy, 288 and grasping, 142 kinematic profiles for setting up and using, 286f mapping, into human and robot hands, 319-24,32Of model, 38-42,344-45 and object properties, 287 and opposition vector, 288f and palm orientation, 103-5, 104f in perturbation studies. 157 phk, 283-86,284f, 285,299-301 planning, 105-7,287-90,299-300,337, 34Of, 341 and reaching, 142 releasing, 278-79,299,300,34Of, 341 setting u 187-91,196-201,290-96,300, 337%. 34Of, 341 state variables, 39,321 Using, 296-99,297f, 300,338-39,34Of, 341 Opposition Space level, 32M, 321,34Uf, 341 Opposition vector and approach vector, 106f, 107, 151,288f definition (equation), 242 and grasp aperture, 145-46 and neural networks, 99f and pad opposition, 242 and planning opposition space, 105,288f use of, 81-8<strong>2.</strong>82f. 107 Oppositions. Opposition; Opposition space OPTOTRAK system, for measuring position coordinates, 127 Orient Palm Schema, 194,195f. 195-96,291f Orientation. see also Orientation, of object of contact point, 235 maps, of a neural network, 97 and opposition space, 103-5.104f
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