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Title: Data-Driven Variable Impedance Control of a Powered Knee-Ankle Prosthesis for Sit, Stand, and Walk with Minimal Tuning
Although the average healthy adult transitions from sit to stand over 60 times per day, most research on powered prosthesis control has only focused on walking. In this paper, we present a data-driven controller that enables sitting, standing, and walking with minimal tuning. Our controller comprises two high level modes of sit/stand and walking, and we develop heuristic biomechanical rules to control transitions. We use a phase variable based on the user's thigh angle to parameterize both walking and sit/stand motions, and use variable impedance control during ground contact and position control during swing. We extend previous work on data-driven optimization of continuous impedance parameter functions to design the sit/stand control mode using able-bodied data. Experiments with a powered knee-ankle prosthesis used by a participant with above-knee amputation demonstrate promise in clinical outcomes, as well as trade-offs between our minimal-tuning approach and accommodation of user preferences. Specifically, our controller enabled the participant to complete the sit/stand task 20% faster and reduced average asymmetry by half compared to his everyday passive prosthesis. The controller also facilitated a timed up and go test involving sitting, standing, walking, and turning, with only a mild (10%) decrease in speed compared to the everyday prosthesis. Our sit/stand/walk controller enables multiple activities of daily life with minimal tuning and mode switching.  more » « less
Award ID(s):
2024237
NSF-PAR ID:
10340009
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems
ISSN:
2153-0858
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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