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Ein Datenschatz für die Ganganalyse: FH St. Pölten und Unfallversicherungsanstalt AUVA öffnen Datenbank für die Forschung
  • France - Français
  • USA - English

St. Pölten University of Applied Sciences Logo (PRNewsfoto/St. Pölten University)

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St. Pölten University of Applied Sciences

Jun 30, 2020, 04:00 ET

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Die Fachhochschule St. Pölten und die Allgemeine Unfallversicherungsanstalt (AUVA) machen einen der größten Datensätze weltweit zur automatisierten Ganganalyse öffentlich. Forscher*innen können die Daten nutzen, um automatisierte Ganganalysen mithilfe von Methoden wie dem Maschinellen Lernen zu verbessern. Der Datensatz und die Beschreibung dazu sind vor Kurzem in der Zeitschrift „Scientific Data" des renommierten Nature-Verlags erschienen.

ST. PÖLTEN, Österreich, 30. Juni 2020 /PRNewswire/ -- „Die Ganganalyse liefert eine Unmenge an Daten. Die Interpretation ist herausfordernd und es besteht großes Interesse daran, die medizinische Entscheidungsfindung mit Verfahren aus dem Maschinellen Lernen zu unterstützen. Je mehr Daten zur Verfügung stehen, umso besser werden die Ergebnisse", sagt Brian Horsak, Leiter des Schwerpunkts Motor Rehabilitation der FH St. Pölten.

Anonymisierte Daten von mehr als 2.000 Patient*innen

Um Forschung, Therapie und Diagnose zu unterstützen, haben Horsak und seine Kolleg*innen von der FH St. Pölten und der AUVA nun einen der größten Datensätze weltweit in anonymisierter Form zu dem Thema veröffentlicht. Die Daten umfassen anonymisierte Informationen von mehr als 2.000 Patient*innen nach Gelenkstransplantationen, Brüchen und Bänderverletzungen sowie damit verbundenen Störungen in Hüfte, Knie, Knöchel und Fersenbein.

Mit den Daten können Analysen und Modelle verbessert werden. Die Datenbank mit dem Namen „GAITREC" ist gratis online verfügbar. Die Daten stammen aus mehreren Jahren an klinischer Praxis in der Ganganalyse.

„Wir haben die Daten gemeinsam mit der AUVA aufbereitet und veröffentlicht. Gerade in der Zeit rund um Corona ist der Datensatz noch interessanter, da viele Expertinnen und Experten keine Daten im Labor aufnehmen können und auf bestehende Datensätze zurückgreifen müssen. Unser Datensatz unterstützt hier sowohl Lehre als auch Forschung", sagt Djordje Slijepčević, Co-Autor und Experte rund um das Thema Maschinelles Lernen an der FH. St. Pölten.

Forschungsschwerpunkt Motor Rehabilitation

Der Forschungsschwerpunkt Motor Rehabilitation an der FH St. Pölten entwickelt technologiegestützte Ansätze der Bewegungsrehabilitation und fördert deren breiten Einsatz in der klinischen Praxis durch die Kooperation mit Partner*innen.

Die FH St. Pölten hat in den letzten Jahren ihre Kompetenzen in den Bereichen der motorischen Rehabilitation, der instrumentierten 3D-Gang- und Bewegungsanalyse, des maschinellen Lernens, der Visual Analytics und im Bereich von Augmented & Virtual Reality ausgebaut und am Standort im Center for Digital Health Innovation (CDHI) verankert. Mit dem Digital Health Lab bietet die FH dazu eines der modernsten Forschungslabore in Österreich.

Die Arbeit zur GAITREC-Datenbank wurden zum Teil von der NÖ Forschungs- und Bildungsges.m.b.H. (NFB) und der Abteilung Wissenschaft und Forschung des Landes NÖ unterstützt.

Publikation "GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait"
Brian Horsak, Djordje Slijepcevic, Anna-Maria Raberger, Caterine Schwab, Marianne Worisch, Matthias Zeppelzauer
Link zum Paper: https://www.nature.com/articles/s41597-020-0481-z 
https://doi.org/10.6084/m9.figshare.12162300

Link zum Datensatz:
https://figshare.com/collections/GaitRec_A_large-scale_ground_reaction_force_dataset_of_healthy_and_impaired_gait/4788012

Schwerpunkt Motor Rehabilitation der FH St. Pölten
https://cdhi.fhstp.ac.at/schwerpunkte/motor-rehabilitation

Logo - https://mma.prnewswire.com/media/1197815/St_Polten_University_Logo.jpg

Kontakt:
Mag. Mark Hammer
T: +43 (0) 2742 313 228 - 269
M: +43 (0) 676 847 228 269
F: +43 (0) 2742 313 228 - 219
E: [email protected]
I: www.fhstp.ac.at

Related Links

https://www.fhstp.ac.at

SOURCE St. Pölten University of Applied Sciences

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