Mechanical Impedance of the Human Hand
Yoky Matsuoka, Aram Hajian, Daniel Sanchez, R. Howe
Support provided by the National Science Foundation and the Office of Naval Research
|Finger and Grasp Impedance|
We have worked to determine how humans modulate the mechanical impedance of
their hands in response to task requirements. The results help explain
sensing and motor control strategies in dextrous manipulation. Our approach
involves experimental measurement of force-motion relationships of the hand
and fingers during task execution. These studies have measured the
impedance of the index finger in extension and abduction, and the impedance
of the precision pinch grasp during lifting.
These measurements form the basis for the biomechanical analysis of
drumming. This task is of particular interest because skilled drummers can
play drum rolls at frequencies well in excess of the usual human motor control
bandwidth. They do this by allowing the drumstick to bounce passively
against the drum head at least twice for each hand stroke. We have obtained
experimental evidence with an instrumented drumstick that drummers control
the bounce frequency by modulating grasp force, which in turn controls the
effective stiffness of the drumstick in its interaction with the drum head.
The results demonstrate that modulation of passive impedance can permit a
low bandwidth manipulator, human or robot, to execute certain types of fast
Learning and Hand Impedance
We have also investigated changes in hand impedance during task learning.
Subjects grasped a handle attached to a haptic interface device, while a
force transient (25 msec duraction) was applied to their hands through the
handle. The force-motion data was used to compute the interacting limb's
impedance instantaneously and accurately (r2=0.98), so time dependent
changes such as adaptation to the task were captured. Using this
technique, we investigated the value of hand stiffness during a task with
precise position requirements. We found that arm stiffness increased and
then saturated with an increase in precision requirements. This stiffness
value at saturation matched intrinsic muscle limitations, and task
performance degraded for precision requirement higher than this saturation
point. In the time domain, stiffness increased and performance improved
rapidly at first, then stiffness decreased slowly over time while
maintaining the performance level.
|Left: Subjects move the end effector of a PHANToM haptic interface robot to
control the vertical position of paddle on the screen. The end effector
contains an accelerometer and force sensor to measure the response to a
fast transient applied to the hand. These data are fit to a second-order
linear model to estimate effective hand mass, damping, and stiffness.
Right: computer screen shows paddle position and ball that enters from
left; subjects control paddle position by moving PHANToM. Increasing the
sensitivity of the paddle motion increases the accuracy requirement.|
A. Z. Hajian and R. D. Howe, "Identification of the mechanical impedance
at the human finger tip," ASME Journal of Biomechanical Engineering
119(1):109-114, Feb. 1997 [Feb. 1997]. Also presented at the International
Mechanical Engineering Congress, American Society of Mechanical Engineers,
Chicago, IL, November 1994, Proceedings ed. C. J. Radcliffe, DSC-vol. 55-1,
A. Z. Hajian, D. S. Sanchez, and R. D. Howe, "Drum roll: Increasing
bandwidth through passive impedance modulation," Proceedings of the IEEE
International Conference on Robotics and Automation, Albuquerque, New
Mexico, April 20 - 25, 1997, pp. 2294-9.
Y. Matsuoka and R. D. Howe, "Hand Impedance Change During Learning of a
Novel Contact Task," 2000 World Congress on Medical Physics and Biomedical
Engineering, Chicago, July 23-28, 2000.
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