Conference paper Open Access

Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion

Guillaume Durandau; Wolfgang F. Rampeltshammer; Herman van der Kooij; Massimo Sartori


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  <identifier identifierType="URL">https://zenodo.org/record/4659993</identifier>
  <creators>
    <creator>
      <creatorName>Guillaume Durandau</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-6951-776X</nameIdentifier>
      <affiliation>University of Twente</affiliation>
    </creator>
    <creator>
      <creatorName>Wolfgang F. Rampeltshammer</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-6703-8765</nameIdentifier>
      <affiliation>University of Twente</affiliation>
    </creator>
    <creator>
      <creatorName>Herman van der Kooij</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7926-3262</nameIdentifier>
      <affiliation>University of Twente</affiliation>
    </creator>
    <creator>
      <creatorName>Massimo Sartori</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0930-6535</nameIdentifier>
      <affiliation>University of Twente</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Myoelectric</subject>
    <subject>exoskeleton</subject>
    <subject>lower-limb</subject>
    <subject>gait</subject>
    <subject>neuromusculoskeletal model</subject>
    <subject>neuromechanic model</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-10-15</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4659993</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/BioRob49111.2020.9224365</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/h2020-sophia</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Individuals with neuromuscular injuries may fully benefit from wearable robots if a new class of wearable technologies is devised to assist complex movements seamlessly in everyday tasks. Among the most important tasks are locomotion activities. Current human-machine interfaces (HMI) are challenged in enabling assistance across wide ranges of locomoting tasks. Electromyography (EMG) and computational modelling can be used to establish an interface with the neuromuscular system. We propose an HMI based on EMG-driven musculoskeletal modelling that estimates biological joint torques in real-time and uses a percentage of these to dynamically control exoskeleton-generated torques in a task-independent manner, i.e. no need to classify locomotion modes. Proof of principle results on one subject showed that this approach could reduce EMGs during exoskeleton-assisted even ground locomotion compared to transparent mode (i.e. zero impedance). Importantly, results showed that a substantial portion of the biological ankle joint torque needed to walk was transferred from the human to the exoskeleton. That is, while the total human-exoskeleton ankle joint was always similar between assisted and zero-impedance modes, the ratio between exoskeleton-generated and human-generated torque varied substantially, with human-generated torques being dynamically compensated by the exoskeleton during assisted mode. This is a first step towards natural, continuous assistance in a large variety of movements.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/803035/">803035</awardNumber>
      <awardTitle>Modelling the neuromusculoskeletal system across spatiotemporal scales for a new paradigm of human-machine motor interaction</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/871237/">871237</awardNumber>
      <awardTitle>Socio-physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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