Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

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Publications (1/1 displayed)

  • 2023Do we still need to screen our patients?—Orthopaedic scoring based on motion tracking1citations

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Jäger, Marcus
1 / 3 shared
Raab, Dominik
1 / 1 shared
Heitzer, Falko
1 / 1 shared
Flores, Francisco Geu
1 / 1 shared
Mayer, Constantin
1 / 1 shared
Müller, Katharina
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Liaw, Jin Cheng
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1 / 1 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Jäger, Marcus
  • Raab, Dominik
  • Heitzer, Falko
  • Flores, Francisco Geu
  • Mayer, Constantin
  • Müller, Katharina
  • Liaw, Jin Cheng
  • Weber, Lina
OrganizationsLocationPeople

article

Do we still need to screen our patients?—Orthopaedic scoring based on motion tracking

  • Jäger, Marcus
  • Raab, Dominik
  • Heitzer, Falko
  • Kecskeméthy, Andrés
  • Flores, Francisco Geu
  • Mayer, Constantin
  • Müller, Katharina
  • Liaw, Jin Cheng
  • Weber, Lina
Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Purpose</jats:title><jats:p>Orthopaedic scores are essential for the clinical assessment of movement disorders but require an experienced clinician for the manual scoring. Wearable systems are taking root in the medical field and offer a possibility for the convenient collection of motion tracking data. The purpose of this work is to demonstrate the feasibility of automated orthopaedic scorings based on motion tracking data using the Harris Hip Score and the Knee Society Score as examples.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Seventy-eight patients received a clinical examination and an instrumental gait analysis after hip or knee arthroplasty. Seven hundred forty-four gait features were extracted from each patient’s representative gait cycle. For each score, a hierarchical multiple regression analysis was conducted with a subsequent tenfold cross-validation. A data split of 70%/30% was applied for training/testing.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Both scores can be reproduced with excellent coefficients of determination <jats:italic>R</jats:italic><jats:sup>2</jats:sup> for training, testing and cross-validation by applying regression models based on four to six features from instrumental gait analysis as well as the patient-reported parameter ‘pain’ as an offset factor.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Computing established orthopaedic scores based on motion tracking data yields an automated evaluation of a joint function at the hip and knee which is suitable for direct clinical interpretation. In combination with novel technologies for wearable data collection, these computations can support healthcare staff with objective and telemedical applicable scorings for a large number of patients without the need for trained clinicians.</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • size-exclusion chromatography
  • hot isostatic pressing