The Grasping Hand

472 Pages·1994·9.559 MB·iii-xvii, 3-482\472

by  Christine L. Mackenzie and Thea Iberall (Eds.)

THE GRASPING HAND
Christine L. MACKENZIE
School of Kinesiology
Simon Fraser University
Burnaby, British Columbia, Canada
Thea IBERALL
Department of Computer Science
University of Southern California
Los Angeles, California, USA
1994
AMSTERDAM LONDON NEW YORK TOKYO
NORTH-HOLLAND
ELSEVIER SCIENCE B.V.
Sara Burgerhartstraat 25
P.O. Box 211, 1000 AE Amsterdam, The Netherlands
Library of Congress Cataloglng-in-Publication Data
MacKenzie, Christine L.. 1951-
The grasping hand / Christine L. MacKen.z ie. Thea Iberall.
p. cm. -- (Advances in psychology 104)
Includes bibliographical references and index.
ISBN 0-444-81746-8
1. Hand--Movements. 2. Hand--Movements--Computer simulation.
3. Motor ability. 4. Hand--Psychophysiology. I. Iberall. Thea.
11. Title. 111. Series Advances in osychology (Amsterdam.
.
Netherlands) 104.
OP334.M 33 1994
612'.97--dc20 93-47 17 1
CIP
ISBN: 0 444 81746 8
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Preface
In the summer of 1985, at a Motor Control conference in
Henniker, New Hampshire, we met and discovered another individual
who shared a fascination (some might say obsession!) about the
human hand. Together, we marvelled at its versatility and its multi-
purpose functionality, and discussed the control problem for dextrous
hands from biological and computational perspectives. But at the
same time, we were astounded by the lack of a coherent, integrative
framework dealing with the hand’s complexities. A common vocabu-
lary was lacking for workers in different disciplines; pockets of
research existed, without overall context. Immediately we saw the
need for a book to bring together knowledge about the hand from
these diverse perspectives. With complementary backgrounds in
computing science and computer engineering (TI) and kinesiology
(CM), we were challenged to integrate the current works on the hand.
The ultimate goal of this book is to identify the underlying func-
tionality of the human hand in prehension. We address two questions:
the question of what is the nature of the human hand and the question
of what might be involved in the CNS as it controls this marvelous
tool in prehension. Our approach is based on the assumption that a
complete model of grasping must be developed and validated both
empirically and computationally. The approach is three-fold: we use
behavioral evidence, biological data, and computational results to
further develop and validate models of prehensile functions. In
contrast to a reductionist approach, we focus on sensorimotor
integration processes, which are more than the simple sum of the
motor and the sensory components.
The significance of such a book is to provide a study of prehen-
sion that is comprehensible to interdisciplinary and multidisciplinary
researchers. Designers of prosthetic and robotic dextrous hands will
find this study useful for developing versatile end effectors.
Practitioners of hand rehabilitation will also gain insights for improv-
ing functionality in injured hands. To motor psychologists, neuro-
physiologists, and kinesiologists, we offer many testable hypotheses,
which we feel can be verified through experiments. For computational
modellers, we provide suggestions for critical inputs and outputs,
identifying areas for future work. Another use is as a textbook for
senior undergraduate and graduate level seminars in diverse fields,
vi THE GRASPINGH AND
including computational neural modelling, motor control, and
cognitive science.
We acknowledge the growing interest and interdisciplinary re-
search into human hand movement. The need for a common vocabu-
lary has been obvious at major symposia and conferences. For ex-
ample, the Canadian Institute for Advanced Research (CIAR)
sponsored a special workshop in London, Canada in May, 1987,
bringing together experts in robotics, artificial intelligence, and human
movement science to share their approaches to prehension (see
Goodale, 1990). Another example was the Dextrous Robot Hand
Workshop in Philadelphia, U.S.A. in April, 1988, at the IEEE
Conference on Robotics and Automation (see Venkataraman and
Iberall, 1990). In both locales, the enthusiastic discussions and
realization of common concerns and goals were offset by the lack of
an integrative framework. Other recent meetings on Hand Function
occurred in Montreal, Canada in May, 1993 and in Ascona,
Switzerland in March, 1994.
We are coauthors in the complete sense: neither one of us alone
could have written this book. Over the last 7 years we have met
together annually, travelling some distance to update this work. One
baby was born, two moves were made from the East to the West coast
of North America, each of us has moved to a new university, and
made other major life changes.
We hope that this book will facilitate effective communication,
and make a contribution toward advancing knowledge on human pre-
hen sion.
vii
Acknowledgements
Many individuals have contributed to this work in many ways.
Thanks to our teachers and mentors, both formal and informal.
Graduate courses were offered at the University of Southern
California and the University of Waterloo, based on earlier drafts of
The Grasping Hand, and we had lively discussions with
colleagues also at Simon Fraser University. We wish to thank our
students, teachers and colleagues for enriching both the seminars and
the book. Thanks to the following individuals for providing feedback
on earlier queries or drafts of the manuscript: Fran Allard, Michael
Arbib, Denise Beattie, George Bekey, Reinoud Bootsma, Phil
Bryden, Heather Carnahan, Sheril Desjardins-Denault, Marcus
Devanandan, Virginia Diggles, Claude Dugas, Andy Fagg, Ken
Goldberg, Evan Graham, Suzanne Halliday, Bruce Hoff, Marc
Jeannerod, Linda Kalbfleisch, Susan Lederman, Gary Lindquist, Ron
Marteniuk, Sean Maw, Chris McManus, John Medley, Ted Milner,
Jacques Paillard, Shahram Payendah, Don Ranney, Eleanor Robbins,
Marg Savage, Barb Sivak, S.T. Venkataraman, Patricia Weir, Richard
Wells, Evelyn Yeo, and Ruth Zemke. For any oversights, we offer
our apologies and thanks.
Thank you to Nikos Apostolopoulos, Elizabeth Carefoot, and
Kathleen Maraj for contributing artwork and graphics, and to Ron
Long and Greg Ehlers for their photographic expertise. Special thanks
to Evelyn Yeo, who, as a summer research student at Simon Fraser
University, cheerfully and competently assisted in compiling
references and figures, and provided model hands. All these
individuals helped to add the aesthetic dimension we wanted.
We wish to acknowledge the support and working environment of
the Departments of Kinesiology and Computer Science at the
University of Waterloo, where this work was initiated. With moves to
the West Coast, we wish to acknowledge at Simon Fraser University
the support of the School of Kinesiology, Centre for Systems Science,
and Instructional Media Centre, and at the University of Southern
California, the Department of Computer Science.
Publishing this work in the Advances in Psychology Series
published by Elsevier Science is, for us, an honor and we wish to
thank George Stelmach and Kees Michielsen for their support and
encouragement.
viii THE GRASPINGH AND
Finally, all our love and thanks to our families and friends for their
faith and for “hanging in” for the seven year period we have been
working on this book. This book was conceived around the same
time as Anne MacKenzie Marteniuk, who at a joyful six years of age,
kept us going at the end with hand poems and drawings. Christie
expresses her love and thanks to Anne and Ron Marteniuk for their
support and patience with “the same time next year” routine. Thea
thanks her parents, sisters, friends, and god for their continued
support, love, and patience.
xiv THE GRASPING HAND
List of Figures
Figure 1.1 Examples of prehension ............................... 5
................................
Figure 1.2 The prehensile problem 7
.........................................
Figure 1.3 Triangle strategy 9
..............................
Figure 2.1 Schlesinger classification 18
....................................
Figure 2.2 Napier classification 24
...................
Figure 2.3 Cutkosky and Howe classification 26
........................................
Figure 2.4 Various postures 28
Figure 2.5 Prehensile postures as oppositions ..................3 2
........................
Figure 2.6 Grasping different sized mugs 33
.....................
Figure 2.7 Virtual fingers apply oppositions 34
...............
Figure 2.8 Jacobson and Sperling coding system 38
Figure 2.9 Virtual finger geometric configuration ...............4 0
Figure 2.10 Black box mapping: object, task, postures .......... 43
Figure 3.1 Wrist velocity and hand aperture .................... S O
Figure 3.2 Velocity and aperture: two objects. ................... 52
.................
Figure 3.3 Arbib Coordinated Control Program 54
Figure 3.4 Paillard model of reaching and grasping. ............5 5
.................................
Figure 3.5 Greene ballpark model 56
................................
Figure 4.1 LAMA robot task plan 66
. ........
Figure 4.2 Miller et al TOTE (Test-Operate-Test-Exit) 68
............................
Figure 4.3 Three major brain systems 71
Figure 4.4 Levels of the CNS ..................................... 73
Figure 4.5 Paillard model of CNS ................................. 74
Figure 4.6 Objects viewed in 2D: pinch vs . clench. .............7 8
.......................................
Figure 4.7 Opposition vector 82
........
Figure 4.8 Neural net for object, task, and oppositions 85
........
Figure 4.9 Neural network for objects and oppositions 88
. .......................
Figure 4.10 Results of Uno et al neural net 89
..........
Figure 4.1 1 Neural network for virtual finger mapping 92
..................
Figure 4.12 Expert system for opposition space 93
.......
Figure 4.13 Kuperstein model for hand-eye coordination 96
..............
Figure 4.14 Iberall approach vector neural network 99
................
Figure 4.15 Iberall approach vector simulations 100
Figure 4.16 Rosenbaum et a1. Orienting wrist for tasks ........ 102
Figure 4.17 Stelmach et al . Orienting opposition space ........1 04
......................................
Figure 4.18 Approach vector 106
Figure 5.1 Coordinated Control Program motor schemas .... 110
........................
Figure 5.2 Homunculus in motor cortex 113
................
Figure 5.3 Computational model of movement 116
List of Figures xv
.....
Figure 5.4 Shape invariance in wrist tangential velocity 124
.....
Figure 5.5 Acceleration and deceleration in aiming tasks 126
.....
Figure 5.6 VITE (Vector Integration to Endpoint) model 129
............
Figure 5.7 Velocity profiles from the VI'IE model 130
Figure 5.8 Jordan network for inverse kinematics ............ 132
Figure 5.9 Learned location sequences for manipulator ...... 134
Figure 5.10 Massone & Bizzi computational model ........... 136
.................
Figure 5.1 1 Generalization capability of model 137
............................
Figure 5.12 Double target experiment 138
. ........................
Figure 5.13 Kawato et a1 learning model 139
. ...........
Figure 5.14 Wrist velocity and aperture vs distance 143
.
Figure 5.15 Movement time for stationary or moving objects 149
Figure 5.16 Aperture for normal and prosthetic hands ......... 150
......
Figure 5.17 Finger and thumb adjustments during pinch 153
Figure 5.18 Mechanical perturbation to pull arm backwards . . 158
.....................
Fiiure 5.19 Perturbation of object direction 160
...........................
Figure 5.20 Perturbation of object size 164
Figure 5.21 Grasping with pad and palm opposition ........... 168
Figure 5.22 Peak aperture and dowel size: pad and palm ...... 170
Figure 5.23 Peak aperture and dowel size: palm, pad and W 172
Figure 5.24 Neural pathways during hand movements ........ 176
.......
Figure 5.25 Kinematics for normal or peripheral vision 180
........
Figure 5.26 Dowel size for normal or peripheral vision 181
Figure 5.27 Kinematics for normal or central vision ...........1 82
........
Figure 5.28 Patient grasping without sensory feedback 186
..................
Figure 5.29 Ballpark for placing mug on table 188
..........
Figure 5.30 Schema model for preshape and enclose 190
.......
Figure 5.3 1 EMG activity during preshape and enclose 193
...................
Figure 5.32 Palm-focused model of grasping 195
.........................
Figure 5.33 Ballpark model of grasping 197
.........
Figure 5.34 Black box: setting up an opposition space 198
............................
Figure 6.1 Structure of hairless skin 208
Figure 6.2 Friction: hysteresis and adhesion ................... 212
.................................
Figure 6.3 Sweat beads on palm 215
Figure 6.4 Sweat discharge on palm ............................ 217
..............................
Figure 6.5 Sweat, friction and grip 221
...........................
Figure 6.6 Mechanoreceptors in skin 223
.........
Figure 6.7 Characteristics of skin mechanoreceptors 225
..................
Figure 6.8 Mechanoreceptors in finger joints 227
......................
Figure 6.9 Exploratory procedures (EPs) 232
Figure 6.10 Hand about to grasp object: object support. ....... 235
...............
Figure 6.11 Point contact and soft finger contact 236
XVi THE GRASPINGH AND
Figure 6.12 Two soft fingers contacting object ................. 238
......................................
Figure 6.13 Multijoint finger 241
Figure 6.14 Applied force and cone of friction .................. 244
........................
Figure 6.15 Two fingers and equilibrium 245
........
Figure 6.16 Apparatus for transducing grasping forces 248
..........
Figure 6.17 Grip and load forces: weight and texture 250
Figure 6.18 Phases in applying grasping forces ................2 51
...............
Figure 6.19 Grasping forces to acquire an object 254
Figure 6.20 Grasping force errors ................................ 257
Figure 6.21 Performatory and exploratory movements ........ 267
..........
Figure 6.22 Hand coordinate frame for manipulation 270
...............
Figure 6.23 Cone of friction and task mechanics 275
......................
Figure 6.24 Baton twirling (from Fearing) 277
Figure 6.25 Black box: using an opposition space. ............. 280
Figure 7.1 Phases: an opposition space analysis ..............2 84
Figure 7.2 Forces and kinematics over all phases ............. 286
............
Figure 7.3 Opposition vector and approach vector 288
...................
Figure 7.4 Palm-focused model of grasping 291
.................
Figure 7.5 Contact: using an opposition space 297
........
Figure 8.1 Levels of mapping for humans and robots 320
Figure 9.1 Black box revisited ................................... 330
....................
Figure 9.2 Levels of mapping, over phases 340
...........................
Figure 9.3 Triangle strategy revisited 342
. ....................................
Figure A 1 Planes of the body 350
..................................
Figure A.2 Upper limb skeleton 352
................
Figure A.3 Bones and joints of hand and wrist 353
...........................
Figure A.4 Descriptions of movement 357
................
Figure AS Dermatome mapping of upper limb 365
. ................
Figure B 1 Prehensile postures: summary view 372
. ......
Figure C.l McCulloch-Pitts neuron vs leaky integrator 385
............................
Figure C.2 Input-output connativity 386
..............................
Figure C.3 Multilayer connectivity 387
Figure C.4 Recurrent nets that are completely connected ..... 388
.........................................
Figure C.5 Learning rules 390
Figure C.6 Generalized delta rule ................................ 393
...................
Figure C.7 Binary and distributed encodings 394
..........................
Figure C.8 Heteroassociative memory 396
...........
Figure C.9 Heteroassociative memory for grasping 398
Figure D.l StanfordJPL hand ................................... 418
FIgure D.2 Utah/MIT hand ....................................... 419
..................................
Figure D.3 Belgrade/USC hand 421
xvii
List of Tables
Table 2.1 Prehensile classifications (alphabetically) ...........1 9
Table 4.1 Training set for neural network ....................... 87
Table 5.1 Percentage of time in deceleration phase ........... 147
..........
Table 6.1 Distribution of eccrine glands in humans 214
..........
Table 6.2 Sensory modalities and object properties 233
...............
Table 6.3 Tactile afferent activity during grasp 255
Table 6.4 Functional strength of postures ..................... 263
Table 6.5 Analytic description of opposition types ........... 266
Table 6.6 Dynamic hand movements in opposition space ...2 72
Table 8.1 Sources of constraints on grasping. ................ 306
Table A .1 Degrees of freedom of the upper limb ............. 354
..............
Table A.2 Joints and muscles of the upper limb 360
......
Table A.3 Innervation of muscles of the upper limb 366
Table B .1 Prehensile classifications (chronologically) .......3 70
..........
Table B.2 Developmental prehensile classifications 376
..............................
Table B.3 Postures as oppositions 378
Table D .1 Commercial prosthetic hooks ....................... 406
..........
Table D.2 Commercial prosthetic mechanical hands 408
............
Table D.3 Commercial prosthetic electrical hands 411
Table D.4 Commercial special devices ......................... 413
...........................
Table D.5 Research prosthetic hands 415