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Robot Control Theory, Virtual Constraints Enable Responsive Powered Prosthesis

Researchers have applied robot control theory and virtual constraints that enable powered prostheses to respond to a wearer’s environment and match the motion of the person as they walk. Experiments with this strategy have shown that amputees wearing the robotic leg are able to walk on a treadmill nearly as fast as a nonamputee.

Powered or robotic prosthetic legs independently control different joints and time periods of the gait cycle but do not have the capability to respond to disturbances or changing terrain. Researchers have proposed addressing this challenge by measuring a single variable that represents the motion of the body—in this case, the center of pressure on the foot that moves from heel to toe during the gait cycle—with the use of virtual constraints, which have demonstrated success in experiments with bipedal robots.

Robert Gregg, PhD

Robert Gregg

Robert Gregg, PhD, assistant professor at the University of Texas at Dallas and UT Southwestern Medical Center, collaborated with researchers at the Rehabilitation Institute of Chicago, Northwestern University and the University of New Brunswick to perform the first application of virtual constraints to define joint patterns of the gait cycle phase during amputee locomotion.

“When the prosthetic leg is in contact with the ground, we are measuring the pressure under the sole of the prosthetic foot, and that pressure moves from the heel to the toe in a strictly increasing manner,” Gregg said. “Measuring where that pressure is tells the prosthetic leg exactly where the human is in the gait cycle, and we can then essentially match the motion of the person.”

Control strategy

Gregg and colleagues tested their control strategy on computer models and then on three transfemoral amputees using the Vanderbilt leg, a powered knee–ankle prosthesis developed at Vanderbilt University that was customized according to the control strategy. Researchers input each user’s height, weight and dimension of the residual thigh into the proposed algorithm and were able to configure the prosthesis for each participant within 15 minutes. Participants then walked on the ground and on a treadmill that moved at increasing speeds.

Participants were able to change their walking speed naturally. “When the subject walks faster, that means that the pressure is going to be moving faster from heel to toe and so the prosthesis knows to accelerate its pattern of its joints,” Gregg said. “The prosthetic leg is actually catching up with the human when he or she increases or decreases walking speed.”

Participants moved at speeds of more than 1 meter per second vs. about 1.3 meter per second in nonamputees. Anecdotally, participants also said they felt less tired after walking on the robotic prosthesis for 2 hours to 3 hours compared with walking on their take-home leg.

“Unfortunately, this was not documented scientifically because we did not do measurements of metabolic energy expenditure,” Gregg said. “It appears that the control strategy is actually contributing energy to the gait cycle instead of users having to compensate for the lack of muscles in the prosthetic leg.”

Metabolic costs

Gregg and his colleagues plan to measure the metabolic costs to scientifically measure whether the control strategy is reducing users’ energy expenditure. They also plan to evaluate the swing period of prosthetic use when the leg is not in contact with the ground and there is no pressure or measurement under the prosthetic foot. “There we have to refer back to more traditional control strategies for the swing period. We are working on ways to improve the swing controller as well so that during the swing motion of the prosthetic leg, it can actually catch up with the user and what he or she is doing with their hips—for example, by measuring the swing motion of the residual thigh,” Gregg said.

He added that the control strategy and prosthesis need to be tested in less structured environments such as on rough terrain or when switching from walking to running. – by Tina DiMarcantonio

References:

Gregg RD. IEEE Trans Robot. 30(6):1455–1471.

YouTube Video: High-Performance Control of a Powered Transfemoral Prosthesis with Amputee Subjects

Disclosure: Gregg reports this study was funded by the U.S. Army Medical Research Acquisition Activity, the Burroughs Wellcome Fund and the National Institutes of Health through the National Institute of Child Health and Human Development.

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