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Integration of instance-based learning and computed torque control for an effective assist-as-needed support in human-exoskeleton interaction
Delgado, Pablo Yihun, Yimesker S. Vangsness, Lisa He, Hongsheng
Delgado, Pablo
Yihun, Yimesker S.
Vangsness, Lisa
He, Hongsheng
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Adobe PDF, 560.03 KB
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Original Date
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Issue Date
2022-12
Type
Article
Genre
Keywords
Assist-as-needed,Human-exoskeleton,Control systems,Nonlinear systems
Subjects (LCSH)
Citation
Delgado, P., Yihun, Y.S., Vangsness, L., He, H. (2022). Integration of instance-based learning and computed torque control for an effective assist-as-needed support in human-exoskeleton interaction. Journal of Management & Engineering Integration, 15(2), 17-25. https://doi.org/10.62704/10057/24821
Abstract
The physiological responses that arise from human-robot interaction may vary across subjects in magnitude and rate. Such individual variations may require instance-based learning over model-based learning algorithms. For instance, a wearable assist-as-needed exoskeleton may require real-time progress data to provide the appropriate level of support to a specific user. In this study, an instance-based learning algorithm was developed and integrated with a computed torque control law. Real-time bio-signals, in the form of electromyography (EMG), were tracked during a predetermined time window to quantify an adaptive threshold value and to control the torque at the exoskeleton joints. These signals were fed to the algorithm, which instantly learned and determined the support needed to accomplish a desired task. The algorithm was tested on a 5-degree-of-freedom wearable exoskeleton used in the automation of upper-limb therapeutic exercises. Results indicated that the algorithm offered the ability to adjust assist-as-needed support instantly based on the amount of muscle engagement present in the combined motion of the human-exoskeleton system.
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Description
Published in SOAR: Shocker Open Access Repository by Wichita State University Libraries Technical Services, November 2022.
Publisher
Association for Industry, Engineering and Management Systems (AIEMS)
Journal
Book Title
Series
Journal of Management & Engineering Integration
v.15 no.2
v.15 no.2
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Archival Collection
PubMed ID
ISSN
1939-7984