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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 manipulation tasks.


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, p. 319-327.

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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