Abstract
We present a method to experimentally identify the inverse dynamics of a human arm. We drive a person's hand with a robot along smooth reaching trajectories while measuring the motion of the shoulder and elbow joints and the force required to move the hand. We fit a model that predicts the shoulder and elbow joint torques required to achieve a desired arm motion. This torque can be supplied by functional electrical stimulation of muscles to control the arm of a person paralyzed by spinal cord injury. Errors in predictions of the joint torques for a subject without spinal cord injury were less than 20% of the maximum torques observed in the identification experiments. In most cases a semiparametric Gaussian process model predicted joint torques with equal or less error than a nonparametric Gaussian process model or a parametric model.
Original language | English (US) |
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Title of host publication | IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3585-3591 |
Number of pages | 7 |
ISBN (Electronic) | 9781479969340 |
DOIs | |
State | Published - Jan 1 2014 |
Event | 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States Duration: Sep 14 2014 → Sep 18 2014 |
Other
Other | 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 |
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Country | United States |
City | Chicago |
Period | 9/14/14 → 9/18/14 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications