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TECHNICAL PAPERS: Joint/Whole Body

Dynamic Motion Planning for the Design of Robotic Gait Rehabilitation

[+] Author and Article Information
Chia-Yu E. Wang

Department of Mechanical and Aerospace Engineering, University of California, Irvine, California 92697

James E. Bobrow

Department of Mechanical and Aerospace Engineering, University of California, Irvine, California 92697jebobrow@uci.edu

David J. Reinkensmeyer1

Department of Mechanical and Aerospace Engineering, University of California, Irvine, California 92697dreinken@uci.edu

1

Also at: Center for Biomedical Engineering, University of California, Irvine, California 92679.

J Biomech Eng 127(4), 672-679 (May 28, 2004) (8 pages) doi:10.1115/1.1979507 History: Received March 27, 2002; Revised May 28, 2004

In this paper we examine a method to control the stepping motion of a paralyzed person suspended over a treadmill using a robot attached to the pelvis. A leg swing motion is created by moving the pelvis without contact with the legs. The problem is formulated as an optimal control problem for an underactuated articulated chain. The optimal control problem is converted into a discrete parameter optimization and an efficient gradient-based algorithm is used to solve it. Motion capture data from an unimpaired human subject is compared to the simulation results from the dynamic motion optimization. Our results suggest that it is feasible to drive repetitive stepping on a treadmill by a paralyzed person by assisting in torso movement alone. The optimized, pelvic motion strategies are comparable to “hip-hiking” gait strategies used by people with lower limb prostheses or hemiparesis. The resulting motions can be found at the web site http://www.eng.uci.edu/∼chwang/project/stepper/stepper.html.

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Copyright © 2005 by American Society of Mechanical Engineers
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Figures

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Figure 1

Step training with body weight support on a treadmill. Two therapists assist in leg movement, while a third assists in torso movement. Reprinted from A. Behrman and S. Harkema (2), with permission of the American Physical Therapy Association.

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Figure 3

Measured passive torque-angle relationships (τst) incorporated into the model

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Figure 4

The resulting gait for Case 1: Paralyzed swing leg with motion captured stance hip orientation (no optimization). The solid lines show the resulting gait and the dashed lines are the gait recorded from the motion capture system.

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Figure 5

The resulting gait for case 2: Unimpaired swing leg. The solid lines show the resulting gait and the dashed lines are the gait recorded from the motion capture system.

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Figure 6

The resulting gait for case 3: Paralyzed swing leg. The solid lines show the resulting gait and the dashed lines are the gait recorded from the motion capture system.

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Figure 7

The resulting gait for case 4: Paralyzed swing leg with bounded stance hip orientation. The solid lines show the resulting gait and the dashed lines are the gait recorded from the motion capture system.

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