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Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning

Caruso, Marco; Sabatini, Angelo Maria; Knaflitz, Marco; Gazzoni, Marco; Croce, Ugo Della; Cereatti, Andrea


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  <identifier identifierType="DOI">10.5281/zenodo.4457500</identifier>
  <creators>
    <creator>
      <creatorName>Caruso, Marco</creatorName>
      <givenName>Marco</givenName>
      <familyName>Caruso</familyName>
      <affiliation>Politecnico di Torino, Turin, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Sabatini, Angelo Maria</creatorName>
      <givenName>Angelo Maria</givenName>
      <familyName>Sabatini</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3306-6498</nameIdentifier>
      <affiliation>The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy; Scuola Superiore Sant'Anna, Pisa, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Knaflitz, Marco</creatorName>
      <givenName>Marco</givenName>
      <familyName>Knaflitz</familyName>
      <affiliation>Politecnico di Torino, Turin, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Gazzoni, Marco</creatorName>
      <givenName>Marco</givenName>
      <familyName>Gazzoni</familyName>
      <affiliation>Politecnico di Torino, Turin, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Croce, Ugo Della</creatorName>
      <givenName>Ugo Della</givenName>
      <familyName>Croce</familyName>
      <affiliation>Università di Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Università de Sassari, Sassari, Italy</affiliation>
    </creator>
    <creator>
      <creatorName>Cereatti, Andrea</creatorName>
      <givenName>Andrea</givenName>
      <familyName>Cereatti</familyName>
      <affiliation>Università di Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Università de Sassari, Sassari, Italy</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-09-21</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4457500</alternateIdentifier>
  </alternateIdentifiers>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4457499</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/mobilise-d</relatedIdentifier>
  </relatedIdentifiers>
  <version>This is the last version of the manuscript that was accepted for publication</version>
  <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;Magneto-Inertial Measurement Units (MIMUs) are a valid alternative tool to optical stereophotogrammetry in human motion analysis. The orientation of a MIMU may be estimated by using sensor fusion algorithms. Such algorithms require input parameters that are usually set using a trial-and-error (or grid-search ) approach to find the optimal values. However, using trial-and-error requires a known reference orientation, a circumstance rarely occurring in real-life applications. In this article, we present a way to suboptimally set input parameters, by exploiting the assumption that two MIMUs rigidly connected are expected to show no orientation difference during motion. This approach was validated by applying it to the popular complementary filter by Madgwick et al. and tested on 18 experimental conditions including three commercial products, three angular rates, and two dimensionality motion conditions. Two main findings were observed: i) the selection of the optimal parameter value strongly depends on the specific experimental conditions considered, ii) in 15 out of 18 conditions the errors obtained using the proposed approach and the trial-and-error were coincident, while in the other cases the maximum discrepancy amounted to 2.5 deg and less than 1.5 deg on average.&lt;/p&gt;

&lt;p&gt;This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union&amp;#39;s Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors&amp;rsquo; view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.&lt;/p&gt;</description>
    <description descriptionType="Other">{"references": ["Caruso, M., Sabatini, A. M., Knaflitz, M., Gazzoni M., Croce, U. D., Cereatti, A. (2020). Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning. IEEE Sensors Journal, 21(3), 3408-3419."]}</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/820820/">820820</awardNumber>
      <awardTitle>Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement</awardTitle>
    </fundingReference>
  </fundingReferences>
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