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  <doc>
    <id>717</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">EMG-Based Validation of Musculoskeletal Models Considering Crosstalk</title>
    <abstract language="eng">BACKGROUND: Validation and verification of multibody musculoskeletal models sEMG is a difficult process because of the reliability of sEMG data and the complex relationship of muscle force and sEMG. OBJECTIVE: This work aims at comparing experimentally recorded and simulated muscle activities considering a numerical model for crosstalk. METHODS: For providing an experimentally derived reference data set, subjects were performing elevations of the arm, where the activities of the contemplated muscle groups were measured by sEMG sensors. Computed muscle activities were further processed and transformed into an artificial electromyographical signal, which includes a numerical crosstalk model. In order to determine whether the crosstalk model provides a better agreement with the measured muscle activities, the Pearson correlation coefficient has been computed as a qualitative way of assessing the curve progression of the data sets. RESULTS: The results show an improvement in the correlation coefficient between the experimental data and the simulated muscle activities when taking crosstalk into account. CONCLUSIONS: Although the correlation coefficient increased when the crosstalk model was utilized, it is questionable if the discretization of both, the crosstalk and the musculoskeletal model, is accurate enough.</abstract>
    <parentTitle language="eng">International Conference BIOMDLORE, June 28 - 30 2018, Białystok, Poland</parentTitle>
    <identifier type="doi">10.1109/BIOMDLORE.2018.8467211</identifier>
    <author>Dominik Jungtäubl</author>
    <author>Maximilian Aurbach</author>
    <author>Maximilian Melzner</author>
    <author>Jan Spicka</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>musculoskeletal modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>validation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>surface electromyography</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>crosstalk</value>
    </subject>
    <collection role="ddc" number="610">Medizin und Gesundheit</collection>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
  </doc>
  <doc>
    <id>8632</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>11</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Taylor &amp; Francis</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Application of a transformer encoder for the prediction of intra-abdominal pressure</title>
    <abstract language="eng">Intra-abdominal pressure is a significant physiological parameter influencing spinal stability and pelvic floor health. This study investigates the potential of a transformer encoder model to predict IAP using motion capture data and musculoskeletal modeling. Data from 211 subjects performing walking, fast walking, and running were used to train a transformer encoder. The model showed promising results with an overall Mean Absolute Percentage Error of 13.5% and a Pearson correlation coefficient of 0.85. Predictions for fast walking and running proved to be more challenging compared to walking, which was attributed to the greater variability and complexity of faster movements.</abstract>
    <parentTitle language="eng">Computer Methods in Biomechanics and Biomedical Engineering</parentTitle>
    <identifier type="doi">10.1080/10255842.2025.2586143</identifier>
    <note>Corresponding author der OTH Regensburg: Mareike Barthel</note>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="Kostentraeger">5200393</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="CorrespondingAuthor">Mareike Barthel</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Mareike Barthel</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Intra-abdominal pressure</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>transformer encoder</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>motion capture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>musculoskeletal modeling</value>
    </subject>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbm">Dendorfer, Sebastian (Prof. Dr.), Zeitschriftenbeiträge - Labor Biomechanik</collection>
    <collection role="oaweg" number="">Hybrid Open Access - OA-Veröffentlichung in einer Subskriptionszeitschrift/-medium</collection>
    <collection role="oaweg" number="">Corresponding author der OTH Regensburg</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
  </doc>
</export-example>
