A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons

Guillaume Durandau, Herman van der Kooij, Massimo Sartori*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Abstract

    Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we created a muscle-driven controller based on electromyography (EMG)-driven musculoskeletal modeling that we interfaced with the robotic bi-lateral Achilles ankle exoskeleton previously developed in our group. Preliminary results on one healthy individual show the possibility of continuously decoding EMG-dependent muscle force and resulting ankle joint moment patterns in real-time across a range of diverse motor tasks. We demonstrate that this information can be used to establish a human-exoskeleton interface with high-resolution at the level of single muscle mechanics.

    Original languageEnglish
    Title of host publicationWearable Robotics
    Subtitle of host publicationchallenges and trends
    EditorsMaria Chiara Carrozza, Silvestro Micera, José L. Pons
    PublisherSpringer
    Pages325-328
    Number of pages4
    ISBN (Electronic)978-3-030-01887-0
    ISBN (Print)978-3-030-01886-3
    DOIs
    Publication statusPublished - 1 Jan 2019

    Publication series

    NameBiosystems and Biorobotics
    Volume22
    ISSN (Print)2195-3562
    ISSN (Electronic)2195-3570

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  • Cite this

    Durandau, G., van der Kooij, H., & Sartori, M. (2019). A computational framework for muscle-level control of bi-lateral robotic ankle exoskeletons. In M. C. Carrozza, S. Micera, & J. L. Pons (Eds.), Wearable Robotics: challenges and trends (pp. 325-328). (Biosystems and Biorobotics; Vol. 22). Springer. https://doi.org/10.1007/978-3-030-01887-0_62