Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements

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dc.citation.articleNumber1127783en_US
dc.citation.journalTitleFrontiers in Neuroroboticsen_US
dc.citation.volumeNumber17en_US
dc.contributor.authorDunkelberger, Nathanen_US
dc.contributor.authorBerning, Jeffreyen_US
dc.contributor.authorSchearer, Eric M.en_US
dc.contributor.authorO'Malley, Marcia K.en_US
dc.contributor.orgMechatronics and Haptics Interfaces Laboratoryen_US
dc.date.accessioned2023-07-21T16:13:52Zen_US
dc.date.available2023-07-21T16:13:52Zen_US
dc.date.issued2023en_US
dc.description.abstractIntroductionIndividuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.MethodsIn this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories.ResultsThe MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone.DiscussionTo realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.en_US
dc.identifier.citationDunkelberger, Nathan, Berning, Jeffrey, Schearer, Eric M., et al.. "Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements." <i>Frontiers in Neurorobotics,</i> 17, (2023) Frontiers Media S.A.: https://doi.org/10.3389/fnbot.2023.1127783.en_US
dc.identifier.digitalfnbot-17-1127783en_US
dc.identifier.doihttps://doi.org/10.3389/fnbot.2023.1127783en_US
dc.identifier.urihttps://hdl.handle.net/1911/114995en_US
dc.language.isoengen_US
dc.publisherFrontiers Media S.A.en_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license.  Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of Fair Use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleHybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movementsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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